UNDERSTANDING THE RELATIONSHIP CULTURE BETWEEN PHYSICIANS AND
NURSES AND THEIR EFFECTS ON PERCEIVED CLINICAL OUTCOMES
AND NURSING OUTCOMES
by
Md Waliullah
A thesis submitted in partial fulfilment
of the requirements for the degree
of
Master’s of Science
in
Industrial and Management Engineering
MONTANA STATE UNIVERSITY
Bozeman, Montana
April 2014
©COPYRIGHT
by
Md Waliullah
2014
All Rights Reserved
ii
DEDICATION
For my mother, Rebeka Khatun, for being the source of my inspiration and
motivation.
For Rifat Tamanna Tinu, thank you for being so patient and having faith in me
during my graduate work. I cannot imagine how difficult it was for you to let your newly
married husband go abroad for graduate study and stay back home alone for two long
years.
iii
ACKNOWLEDGEMENTS
I sincerely pray and thank almighty Allah for the successful completion of my
graduate works. All the credits and praises are only for Him who has created the heavens
and earth, who is the most merciful and the most beneficent.
To Dr. William Schell, thank you for guiding me all the way towards the
completion of my thesis work with patience. Thank you for providing me all the
necessary materials at immediate notice to develop the survey instrument and analysis of
the data. I cannot think of completing this work without your consistent support for last
two years. I am privileged to have you as the co-chair of my thesis committee.
To Dr. Nicholas Ward, thank you for accepting me as your thesis student and
motivating me to pursue my thesis on this excellent topic. Thank you for guiding me,
correcting my concepts and understanding throughout the process. You were a major
motivating factor during my graduate work.
To Dr. Susan Luparell, from the College of Nursing, thank you for your
remarkable assistance for the development of the survey instrument, conducting presurvey with the students of college of nursing and guiding me all the way toward the
completion of my thesis work. Without your assistance in gaining access to participants,
completion of this dissertation would have been impossible.
To Dr. Durward Sobek and Dr. David Claudio, thank you for your time and
feedback during the development process of the survey instrument. Thank you William
Hamel and Toni Rule for assisting me with the collection of participants’ responses. I
also thank all the others who have helped me in many occasions during the graduate
works.
iv
TABLE OF CONTENTS
1. INTRODUCTION .......................................................................................................... 1
2. LITERATURE REVIEW ............................................................................................... 5
Summary of Literature Review and Gaps in Previous Works ...................................... 10
Social Norms Theory in Behavioral Study ................................................................... 13
Example 1: Reducing Alcohol Consumption in Pregnant Women ...................... 15
Example 2: Reducing Drinking and Driving ........................................................ 16
3. RESEARCH STATEMENT ......................................................................................... 17
Research Question and Conceptual Model ................................................................... 18
Rationale and Contribution ........................................................................................... 23
4. METHODOLOGY ....................................................................................................... 26
Instrument Design and Rationale .................................................................................. 26
Rationale for Selecting Survey Method ................................................................ 29
Validation of the Instrument ................................................................................. 30
Experiment Setting and Subjects .................................................................................. 31
Sampling Strategy ................................................................................................. 31
Data Collection.............................................................................................................. 34
Data Analysis Plan ................................................................................................ 35
Ethics and Protection of Human Subjects ..................................................................... 36
5. DATA ANALYSIS AND RESULTS........................................................................... 37
Demographic Analysis of the Study Data Sets ............................................................. 37
Data Analysis ................................................................................................................ 39
Examination of Hypothesis – 1 ............................................................................. 40
Conclusion of Cluster Analysis ................................................................ 45
Hypothesis 2 – Actual vs Perceived Norms of Relationship Culture ................... 45
Hypothesis 2 – Actual vs Perceived Descriptive Norms .......................... 46
Hypothesis 2 – Actual vs Perceived Injunctive Norms ............................ 50
Hypothesis 2 – Actual vs Perceived Behavioral Norms (SPB) ................ 52
Hypothesis 2 – Actual vs Perceived Behavioral Norms (DPB)................ 53
Summary of Results for Hypothesis 2 ...................................................... 54
Hypothesis 3 – Descriptive vs Injunctive Norms ................................................. 55
Hypothesis 4 – Impact of Behavioral Norms on Nursing Outcomes ................... 56
Hypothesis 5 – Impact of Behavioral Norms on Clinical Outcomes .................... 57
v
TABLE OF CONTENTS - CONTINUED
Additional Findings ....................................................................................................... 58
Do Physicians Display Supportive Behaviors Toward Nurses? ........................... 59
Do Physicians Display Disruptive Behaviors Toward Nurses?............................ 61
Effects of Physicians Behaviors on Nursing Outcomes ....................................... 62
Effects of Physicians Behaviors on Clinical Outcomes........................................ 63
6. CONCLUSION AND DISCUSSION........................................................................... 64
Hypothesis Testing Results and Contribution ............................................................... 65
Discussion and Theoretical Implications of the Study .................................................. 68
Limitations of the Study ................................................................................................ 70
Areas for Future Works and Recommendations ........................................................... 72
REFERENCES CITED ..................................................................................................... 75
APPENDICES .................................................................................................................. 81
APPENDIX A: Definition of Key Terms Related to SNT ................................... 82
APPENDIX B: Approval of Institutional Review Board ..................................... 87
APPENDIX C: Demographic Information ........................................................... 90
APPENDIX D: Normality Test of Study Data Sets.............................................. 93
APPENDIX E: Cluster and Factor Analysis For Hypothesis 1 ............................ 95
APPENDIX F: Data Analysis Using 2-Sample t-Test & 2-Proportions Test ..... 120
APPENDIX G: Results of Additional Findings.................................................. 158
APPENDIX H: Recommended Instrument ........................................................ 163
vi
LIST OF TABLES
Table
Page
1: Findings of Rosenstein and O’Daniel ................................................................8
2: Findings of Schmalenberg and Kramer on RN-MD Relationship style...........12
3: Proposed outline lottery incentive program .....................................................35
4: Statistics of Survey Mail and Responses..........................................................38
5: Clusters of RN Data Sets and associated Cronbach's Alpha value ..................45
6: Results on 'Physician as Teacher' .....................................................................49
7: Results of Hypothesis 2 (Descriptive Norms) ..................................................51
8: Actual vs Perceived Interpersonal Norms - % of Selected Response ..............51
9: Results of Hypothesis 2 (Injunctive Norms) ....................................................52
10: Injunctive norms of RN and MDs - % of selected responses.........................52
11: Results of Hypothesis 2 (SPB) .......................................................................54
12: SPB - % of selected responses .......................................................................54
13: Results of Hypothesis 2 (DPB) ......................................................................55
14: DPB - % of selected responses .......................................................................55
15: Results of Hypothesis 3 (Descriptive vs Injunctive Norms) ..........................57
16: Results of hypothesis 4 (Impact on Nursing Outcomes) ................................58
17: Impact of physician behavior on nursing outcomes .......................................58
18: Results of hypothesis 5 (Impact on Clinical Outcomes) ................................59
19: Impact of physician behavior on perceived clinical outcomes ......................59
vii
LIST OF FIGURES
Figure
Page
1: Types of norms and their interconnections ........................................................15
2: Conceptual Model of Study ...............................................................................21
3: Cross-Evaluation Strategy of Different Relationship Norms ............................22
4: Demographic Summary .....................................................................................40
5: Physicians as teacher - Actual Norms of RN and MD ......................................48
6: Physician as Teacher - Actual vs Perceived Norms of RN................................48
7: Physician as Teacher - Actual vs Perceived Norms of MD ...............................48
8: Physicians as Teacher - Perceived Norms of RN and MD ................................48
9: % of RNs reported 'most' to 'everyone' of MDs displayed SPB ........................62
10: % of MDs reported 'Usually' to 'Always' regarding displaying SPB ...............62
11: % of RNs reported 'No Physician' displayed disruptive behaviors..................63
12: % of MDs reported 'Never' regarding displaying DPB ...................................63
viii
ABSTRACT
The US healthcare industry faces a variety of complex challenges.
Simultaneously, pressures continue to mount with regard to the expectation for lower
costs with improved quality of care. These problems have drawn the attention of many
researchers seeking ways to improve healthcare delivery. These efforts regularly identify
two key issues requiring solutions: 1) Improving clinical outcomes by reducing adverse
patient conditions due to medical errors, and 2) Improving care delivery by reducing
staffing shortages and turnover within the nursing profession. Several studies have shown
that workplace culture and incivility can be a material contributor to both of these issues.
While many researchers have investigated the nature of nurse-physician interaction, and
their effects on clinical and nursing outcomes, they mostly focus on the ‘perception’ of
nurses and not physicians. Perhaps more importantly, these studies generally did not
distinguish between descriptive and injunctive norms suggested by Social Norms Theory
(SNT). This study seeks to close both of these gaps. This study developed a new survey
instrument to measure these norms and performed a sample survey of the physicians and
nurses of Montana and Denver area. This study used SNT to identify any gaps between
descriptive and injunctive norms of RNs and MDs regarding their relationship culture and
their effects behaviors on perceived nursing outcomes (e.g. job satisfaction, retention,
etc.) and perceived clinical outcomes (e.g. medical errors, quality of care). The study
sought to investigate these gaps because SNT suggests that people tend to behave in the
way they believe is most typical of and accepted by their peers (perceived norms).
Unfortunately, perceptions of others’ behaviors are quite frequently inaccurate, with
views of problematic behaviors tending to be overestimated and healthy behaviors
tending to be underestimated. SNT offers an innovative approach for addressing such
situations by changing perceptions. The findings of the study suggest significant
differences between the perceived norms of physicians and nurses when compared to
their actual norms. The findings are expected to be helpful for developing an intervention
program to improve the relationship culture between physicians and nurses which can
contribute to improve quality of patient care and nursing retention.
1
INTRODUCTION
The nature of the relationship between nurses and physicians has evolved
throughout the years. In the early 1900s, nurses were viewed as physicians’ handmaidens
who were reliant upon physicians for knowledge and approval, and were expected to
perform with unquestioning obedience (Morey, 2006). During the 1940s, nurses started
expressing a desire to separate nursing care from medical care and moved toward
improved nursing education as evidenced by nurses teaching nurses, and implementation
of autonomy of practices within the nursing profession (Morey, 2006). However, these
developments were not always favorably received by many physicians as they perceived
nurses were becoming overly educated (Peplau, 2007). Regardless, nursing has continued
to advance as a profession to the point where nursing now sees itself as a united
profession of highly educated individuals who have an audience with government
(Fletcher, 2000). Today many physicians accept nursing as a profession that
complements medicine and view nurses as having an equally important but different
knowledge base (Kramer & Schmalenberg, 2003). The realization of the importance of
nursing as a profession and consequently the importance of healthy nurse-physician
relationship has increased within the members of healthcare organizations including
physicians, nursing supervisors and healthcare administrators. This importance can be
better realized by the prestigious ‘ANCC Magnet Recognition Program’ of American
Nurses Credentialing Center (ANCC) to recognize healthcare organizations for quality
patient care, nursing excellence and innovations in professional nursing practice (ANCC,
2014). Among the eight (8) characteristics of Essentials of Magnetism (EOM), ‘building
2
and maintaining good nurse-physician relationship’ has been identified as the first
essential to qualify for the Magnet Recognition program (Kramer & Schmalenberg,
2004). Unfortunately, at present, there is significant evidence in the literature suggesting
that nurse-physician relationships are not completely satisfying to nurses (Shen et al,
2010; Rosenstein, 2002; Sirota, 2008; Schmalenberg & Kramer, 2009; Friese &
Manojlovich, 2012; Rossenstein, Russell, & Lauve, 2002) and as a result, quality of
patients’ care is often being compromised (Houle, 2001; Rosenstein, 2002).
The U.S. healthcare industry is currently facing a variety of complex challenges,
including an aging population and increases in chronic disease. According to
Administration of Aging (AOA, 2014), the total number of older population (age 65 or
over) in United States was 39.6 million in 2009 (12.9% of total population). By 2030, it is
expected to increase by 72.1 million which would be (19%) of total population. The
Centers for Disease Control and Prevention estimated that 75% of total health care
expenses goes to treatment of chronic diseases in USA (CDC, 2014). In addition, the
healthcare industry continues to come under ever greater scrutiny and pressure to deliver
top quality care at lower costs. As the expectations for the healthcare industry are rising,
many researchers are investigating different means by which achieve quality of patient
care at lower costs. Two key issues frequently examined are adverse patient outcomes
due to medical errors and staffing shortages caused by high levels of turnover within the
nursing profession (Rosenstein & O'Daniel 2005, Schmalenberg & Kramer 2009). These
studies have identified one element that appears to be causal for both of the issues – the
culture of the workplace with regard to the relationship between physicians and nurses
3
(Rosenstein, 2002; Schmalenberg & Kramer, 2009). A number of RNs reported (in
different studies) disruptive physician behaviors as a threat to quality of patient care
(Shen et al, 2010; Rosenstein A.H, 2002; Sirota, 2008; Schmalenberg & Kramer, 2009;
Friese & Manojlovich, 2012), nurse retention within the profession (Shen et al, 2010;
Rosenstein A.H, 2002; Sirota, 2008; Friese & Manojlovich, 2012) and effectiveness of
nurses’ practices (IOM, 1999; Rosenstein A.H, 2002; Schmalenberg & Kramer, 2009;
Sirota, 2008). Not only have incivility and disruptive behavior been associated with
decreased satisfaction and increased nurse turnover (Vessey, 2010), they recently have
been linked specifically to negative patient outcomes, including serious injury and death
(ISMP, 2004; Joint Commission, 2008, 2012; Rosenstein, 2005). In a landmark report,
To Err Is Human, the Institute of Medicine (IOM) estimated at least 44,000 and perhaps
98,000 hospitalized patients die every year due to preventable medical error (IOM, 1999).
Beyond the cost in human lives, preventable medical errors exact other significant tolls.
They have been estimated to result in total costs (including the expense of additional care
necessitated by the errors, lost income and household productivity, and disability) of
between $17 billion and $29 billion per year in hospitals nationwide (IOM, 1999).
Several reasons for medical error identified by IOM are related to the safety culture of
workplace, these include communication failure, avoidable delays in treatment, error in
procedure and the organizational system. IOM has emphasized on building better
relationship among physicians, nurses and administrative executives in order to develop a
robust safety culture.
4
Disruptive behaviors towards nurses in the workplace has been identified as a
contributing factor to low retention within the profession and lower job satisfaction of
nurses (Shen et al., 2010; Rosenstein A.H, 2002; Sirota, 2008; Friese & Manojlovich,
2012). The negative impact of nursing turnover is illustrated by the forecasted shortfall of
nurses in the U.S. identified in different studies. In 2001, the American Hospital
Association (AHA) estimated that 126,000 nursing positions were unfilled in the United
States (AHA, 2001). In a recent document, ‘Workforce 2015: Strategy Trumps Shortage’,
the AHA (2010) quoted the estimation of Peter Buerhaus and colleagues at Vanderbilt
University who projected a shortfall of registered nurses in 2025 as 260,000. Another
study by Juraschek and colleagues estimated the shortfall of RNs would be as high as
1,000,000 by 2030 (Juraschek et al., 2012).
This study investigated the relationship culture between physicians and nurses as
experienced and perceived by the RNs and MDs. This study also sought to investigate the
norms of supportive and disruptive physician behaviors and their effect on clinical
outcomes (quality of care, adverse events, and medical errors.) and nursing outcomes (job
satisfaction, turnover) as perceived and experienced by the RNs and MDs. In order to do
so, the research team conducted an extensive survey of RNs and MDs throughout
Montana and the Denver, Colorado area. The responses of the RNs and MDs were
critically analyzed and compared to get more detailed perspectives. The data collection
and investigation process utilized the concept of Social Norms Theory (SNT) to explore
differences between actual and perceived norms as well as descriptive and injunctive
norms of RNs and MDs. The researchers expect that the findings of this survey should
5
enable development of an intervention program that will improve nurse-physician
relationships and nursing job satisfaction as well as reduce medical error.
6
LITERATURE REVIEW
Relationships between physicians and nurses are important for several reasons.
How well these two groups work together affects the quality of care that patients receive
(Baggs et al., 1992). Schmalenberg & Kramer (2009) quoted a classic study conducted by
Knaus et al. (1986) on intensive care units (ICUs) in 13 large hospitals nationwide that
reported ICU patients cared for by nurses and physicians who worked collaboratively had
lower acuity-adjusted mortality rates than did patients cared for by less collaborative
nurses and physicians. Fewer deaths and fewer transfers back to the ICU are positive
outcomes for patients that have been associated with high quality nurse-physician
relationships as cited in other studies (Schmalenberg & Kramer 2009, Larson 1999,
Baggs et al. 1999). In addition to patient outcomes, high-quality nurse physician relations
result in increased satisfaction among nurses and physicians, and increased autonomy for
nurses (Schmalenberg & Kramer, 2009). These findings are also supported by many other
researchers (e.g. Rossenstein, 2002; Sirota, 2008; Shen, Chiu, Lee, Hu, & Chang, 2010;
Schmalenberg & Kramer, 2009)
One of the major challenges in the US healthcare industry is the high turnover rate
of nurses. In 2001, the American Hospital Association (AHA) estimated that 126,000
nursing positions were unfilled in the United States (AHA, 2001). In a recent document,
‘Workforce 2015: Strategy Trumps Shortage’, the AHA quoted the estimation of Peter
Buerhaus and colleagues at Vanderbilt University who projected a shortfall of registered
nurses in 2025 as 260,000 (AHA, 2010). Another study by Juraschek et al. estimated the
shortfall of the RNs would be as high as 1,000,000 by 2030. (Juraschek, Zhang,
7
Ranganathan, & Lin, 2012). Nursing shortage affects quality of care, services have been
reduced, surgeries canceled, and units closed in many facilities (Rossenstein A. H., 2002;
Fackelmann, 2001; Lovern, 2001). Concurrently, patient care and patient safety have
been compromised and rates of medical errors have risen (Houle, 2001). A variety of
reasons for the shortage have been cited: an aging workforce, fewer nursing school
programs and admitted applicants, hospital restructuring , poor public perceptions of
nursing as a career and rising burnout and job dissatisfaction among nurses (Rossenstein
2002; Buerhaus, 2000). Allan Rosenstein (2002) conducted an extensive study on nursephysician relationship by surveying 1200 participants from 84 hospitals or medical group
that included mostly nurses, but also physicians and administrative executives. In this
study, almost all nurses’ reported of experiencing disruptive behaviors by physicians,
though a small percentage of physicians reported exhibiting disruptive behavior. Both
physicians and nurses agreed that the disruptive behaviors might impact the nurses’ job
satisfaction and retention. They also reported that disruptive behaviors impacted the
efficiency, accuracy, safety and outcomes of care. In this study, nurses indicated
disruptive behaviors by physicians occurred most commonly –
o After placing calls to physicians
o After questioning/seeking to clarify physicians orders
o When physicians thought their orders were not being carried out correctly or in a
timely manner
o After perceived delays in delivery of care
o After sudden changes in patient status.
8
The above examples indicate that disruptive behaviors to nurses may occur at any
point of nurses’ interaction with physicians and this occurrence does not depend on any
specific situation or patient condition.
In a later survey by Rosenstein and O’Daniel (2005), nurses, physicians and
hospital administrators were asked how often they thought (i.e., perceived) there was a
link between disruptive behavior and different clinical outcomes. A significant number of
respondents reported ‘sometimes’, ‘frequent’ or ‘constant’ link between disruptive
behaviors and all clinical outcomes except for patient mortality. Table 1 summarizes the
findings of Rosenstein and O’Daniel (2005). It demonstrates the percentage of
respondents answering 'Sometimes', 'Frequently' or 'Constantly' to question ‘how often do
you think there is a link between disruptive behavior and clinical outcomes’. These
findings provide strong evidence regarding the relationship between disruptive behaviors
in workplace and perceived clinical outcomes.
Clinical Outcomes
Table 1: Findings of Rosenstein and O’Daniel
Physicians
Nurse
Administrator
Adverse Events
60%
68%
80%
Errors
62%
73%
80%
Patient Safety
49%
54%
80%
Quality of care
67%
73%
73%
Patient Mortality
26%
25%
27%
Patient Satisfaction
71%
77%
88%
9
In a recently survey of 170 nurses from a medical-surgical unit (MSU) (54%) and
intensive care unit (ICU) (46%), 57% of the nurses responded they had witnessed
disruptive behavior by physicians (Johnson & Kring, 2012); however, a minority (26%)
noted that they had reported disruptive behavior. In addition, the ICU nurses (80%) were
found more likely to report disruptive physician behaviors than their MSU counterparts
(58%). Overall 70% nurses reported they were ‘satisfied’ with their professional
relationships to physicians and 57% nurses reported ‘seeing’ disruptive behaviors by
physicians. Another survey of 900 nurses in 2008 explored similar results regarding
nurses’ satisfaction of nurse-physician relationship. Here 74% nurses reported being
‘moderately’ to ‘more satisfied’ and 26% reported being ‘moderate’ to ‘more dissatisfied’
(Sirota, 2008). Two-thirds (67%) of the nurses in this survey reported they had witnessed
disruptive behaviors by physicians in the past year. In another large, nationwide study,
96% of the 714 nurses surveyed indicated that they had either experienced or witnessed
abusive behavior, and 31% indicated hostile nurse-physician relationships existed (Sirota,
2008). The bottom-line of all these studies is that disruptive physician behaviors exist and
they adversely impact nursing job satisfaction which can result in low retention and lower
quality of patient care.
The nurse-physician relationship is also an important determinant for quality of
care as perceived by patients (Shen et al, 2010), nurses (Shen et al, 2010; Rosenstein
A.H, 2002; Sirota, 2008; Schmalenberg & Kramer, 2009; Friese & Manojlovich, 2012),
physicians (Rosenstein A.H, 2002; Sirota, 2008; Schmalenberg & Kramer, 2009) and
administrative executives (Rosenstein & O'Daniel, 2005; Rossenstein A. H., 2002). Thus,
10
researchers have explored the nature of relationship culture of these professions and
examined diffferent factors (e.g., age, gender, experience, race, workload, authority) that
might influence the relationship in order to find ways to improve it. For example, studies
have been conducted to explore the effect of gender on nurse-physician behavior. The
influence of physician’s gender on nurses’ behavior toward physicians was examined in a
survey of 265 nurses of urban hospitals in Canada (Zelek & Phillips, 2003). The study
found that nurses do more for male physician but expect more of female physicians.
Findings also suggest that nurses are more resistant to domination by female, rather than
male doctors. Other studies find that nurses generally experience greater satisfaction
when communicating with female rather than male physicians (Glenn, Rhea, & Wheeles,
1997) and prefer a female managerial style (Camden & Kennedy, 1986) as quoted by
Zelek and Phillips (2003). These studies give evidence that gender of physicians and
nurses is one of the influencing factors on the nature of RN-MD relationship.
Perhaps the most extensive and organized work exploring the nature of nursephysician relationship culture was conducted by Schmalenberg and Kramer (2009). In a
six-year long study, they examined the findings from six different research projects.
These projects included a Magnetism study, a psychometric study and four interview
studies that pertain to nurse-physician relationships. The participants in all six studies
included a total of 20,616 staff nurses, 334 nurse managers, 229 physicians and 46
hospital administrators or other health professionals. They identified five different types
of relationship that exists between nurses and physicians – Collegial, collaborative,
student-teacher, friendly-stranger and hostile/adversarial. In the study, they found
11
multiple relationships coexist on a sample clinical unit; i.e. a nurse may have a
collaborative relationship with one physician, a hostile relationship with another and a
student-teacher type relationship with a third. The findings from their studies (both 2003
and 2007) are summarized in Table 2. The value in this table indicated the percentage
(%) of nurses reported the type of relationship they had with physicians. Note that, in
2003 study, the number of accepted responses were 3602 staff nurses from 16 magnet
and 10 non-magnet comparison hospitals. And in 2007 study, the number of accepted
responses were 10,514 staff nurses from 18 magnet and 16 non-magnet comparison
hospitals. From the findings of Schmalenberg and Kramer (2009), it is evident that most
nurses reported favorable relationship with physicians. However, it also shows that
undesirable relationships exist between physicians and nurses in both type of hospitals.
Summary of Literature Review
Previous studies illustrate the importance of RN-MD relationship culture and its
potential impact on nursing and clinical outcomes. They also show that disruptive
physician behaviors toward nurses exist in workplace and they have adverse effects on
nursing outcomes (e.g., job satisfaction, turnover, retention within the nursing profession)
and clinical outcomes (e.g. adverse patient condition, delays in care, quality of care) as
reported by mostly nurses, physicians and hospital administrators.
12
Table 2: Findings of Schmalenberg and Kramer on RN-MD Relationship style
(Reproduced with permission)
Hospital Type
Relationship Type
Magnet (%)
Comparison (%)
Collegial
2003
86
61
2007
81
75
Collaborative
2003
82
64
2007
85
80
Student-Teacher (Physician in Teaching role)
2003
69
54
2007
78
74
Student-Teacher (Nurse in Teaching role)
2003
66
49
2007
67
62
Friendly-Stranger
2003
54
63
2007
59
59
Hostile/adversarial
2003
13
29
2007
17
20
These studies have investigated either the ‘perception’ of participants or their
‘actual experience’ regarding disruptive physician behaviors and the relationship to
clinical and nursing outcomes. Additionally, the studies that explored the nature of RNMD relationship have mostly investigated the perception of the participants, not the
actual experience of each individual. The participants of these studies were mostly nurses
and rarely physicians. Besides, as the studies have mostly focused on investigating the
‘perception’ of nurses (and physicians in few cases) and did not compare the ‘perception’
with the ‘actual experience’ of individual participants, the findings may not correctly
represent the RN-MD relationship culture and its impact on clinical/nursing outcomes.
13
Thus the pictures of RN-MD relationship culture that these studies have explored fall
short of portraying the complete story. Since perceptions of others’ behaviors are quite
frequently inaccurate, with views of problematic behaviors tending to be overestimated
and healthy, protective behaviors tending to be underestimated, a phenomenon known as
“pluralistic ignorance” (as cited by Berkowitz, 2005). For example, overestimations and
misperceptions have been identified in a number of population including high school
popopulations (Hansen & Graham, 1991), adolescents in middle schools (Perkins, Craig,
& Perkins, 2011), statewide populations of young adults (Linkenbach 1999, Linkenbach
& Perkins 2003) and pregnant women (Dunnagan et al., 2007). These findings suggests
the possibility that a misperception may exist among the population of RNs and MDs
regarding the their relationship culture, disruptive behaviors and its impact on clinical
and nursing outcomes. Physicians may display incivil behaviors because it is mistakenly
assumed that such behavior is commonplace and accepted. In contrast, some behavior
may be overrated or overly common in people’s belief; but in reality, they are rarely
practiced. For example, physicians were to blame for a large part of disruptive behaviors
to nurses in clinical environment (Clinical Rounds, 2010), though the reasons for
disruptive behaviors were multi-factorial and include workload, nursing shortage,
organizational culture, administration etc.
Social norms theory offers an innovative approach for addressing such situations
by changing perceptions and modifying beliefs (PCN Overview 2012, Dunnagan et al.
2007). However, before this effort can be initiated, investigators must first see if the
misperception exists. Appendix A describes the definition of some key terms related to
14
social norms theory, i.e. actual norms, perceived norms, descriptive norms, injunctive
norms etc.
Social Norms Theory in Behavioral Study
The Social Norms Theory (SNT) suggests that people tend to behave in the way
they believe is most typical of and accepted by their peers, that is the perceived norms
(Berkowitz, 2005). It further predicts that individuals will alter their behavior for the
better by correcting misperceptions and revealing the true norms. As mentioned in the
introduction, this study uses SNT framework to investigate the RN-MD relationship
norms and its impact on nursing and clinical outcomes. The social norms approach
measures an individual’s perceptions of different norms for a specific behavior or attitude
as well as the actual behavior or attitude (true norms). This methodology measures the
gap between the two and its influences on behavior (Perkins & Berkowitz, 1986). Some
key terms related to SNT are explained below.
Actual Norms: Actual norms, also known as social norms, are the behaviors or
attitudes of the majority of people in any community or group (PCN Overview, 2012). If
most people in a community do not drink, then not drinking is the ‘normative’ behavior,
or the actual norm. Not drinking is normal, acceptable, and perhaps even expected in that
population. Let’s consider Kathy is a registered nurse working in a hospital ‘X’. If she
finds all the physicians are cooperative to her, then ‘Physicians are cooperative’ is her
actual norm. The collection of this ‘actual norms’ (i.e. the collective actual experience) of
all the nurses of hospital ‘X’ is the ‘actual social norms’ of the RNs of that hospital.
15
Perceived Norms: Perceived norms, also known as peer norms or perceptions of
social norms, are people’s beliefs about the norms of their peers. If a group of people
think that most other people drink and drive, then drink and drive would be their
perceived norms. Consider the example of Kathy – if she thinks that most physicians are
not cooperative toward other nurses, or if she thinks that most other nurses believe
physicians are not cooperative toward them, then ‘Physicians are not cooperative toward
nurses’ is her perceived norm.
Figure 1: Types of norms and their interconnections
Descriptive and Injunctive Norms: Actual and perceived norms can be both
descriptive and injunctive in nature. Injunctive norms capture people’s attitudes, in
particular, a sense of disapproval (“this is wrong”) or an injunction (“should” or “should
not”). Examples of injunctive norms are ‘most people think it is wrong to steal” or “most
people believe they should exercise regularly’ (PCN Overview, 2012). In contrast,
Descriptive norms describe the behaviors of people as opposed to their attitudes.
Examples of descriptive norms are ‘most people eat lunch every day’ or ‘most students
do their homework’ (PCN Overview, 2012). The examples of Kathy given above
16
demonstrate descriptive norms. If Kathy thinks that physicians should always be
cooperative toward all nurses, then her actual injunctive norm would ‘Physicians should
always be cooperative toward nurses’. If Kathy thinks that most other nurses believe that
physicians should be cooperative towards them when necessary, then her perceived
injunctive norm would be ‘Physicians should be cooperative toward nurses as necessary’.
Appendix A demonstrates these definitions with detail examples.
Social norms theory was found successful in achieving behavioral changes in
many cases (Perkins et al. 2010, Dunnagan et al. 2007, Linkenbach and Perkins 2003,
Hansen and Graham 1991). To illustrate how SNT works and why the study of different
norms are important, two examples are presented below.
Example 1: Reducing Alcohol
Consumption in Pregnant Women
Dunnagan et al. ( 2007) used SNT to develop an intervention strategy to reduce
alcohol consumption in pregnant women. They surveyed 712 women base on social
norms theory. Results revealed that prior to the pregnancy women perceived that other
women of their same age normally drank more than four times as much alcohol as they
actually consumed. However, during their pregnancy women perceived that other women
of their same age normally drank over 102 times as much alcohol as they actually
consumed. Similar patterns were seen for the more than usual consumption. The results
of the investigation showed a consistent and dramatic pattern of overestimation of peer
alcohol use norms compared to actual norms. These findings supported the application of
17
intervention strategies designed to correct misperceptions of drinking norms in pregnant
women as a way to reduce actual drinking rates.
Example 2: Reducing Drinking and Driving
Perkins et al. (2010) performed a statewide media campaign in order to reduce
drinking and driving among 21-to-34 years-olds in the state of Montana. They used a
survey based on social norms theory to measure the behavioral norms and to develop the
intervention strategy. In their survey, before the intervention program, 91.8% of the
participants reported that they believed average Montanan drove within one hour of
consuming two or more drinks in past month. However, only 22.9% of the participants
responded ‘yes’ to the question that they drove after consuming two or more drinks
within an hour in past month. It reflects a major misperception of the peer norms
regarding the risky behavior. The researchers conducted a media campaign promoting the
safe behavior as explored from the survey. The main message of the campaign was ‘Most
of us (4 out of 5) don’t drink and drive’ or ‘most of us keep designated driver if they
drink’ and something similar to this. After 15 months of extensive media campaign, a
reduction of 7.5% in the peer norms and 13.7% in actual behavior of drinking and driving
was reported in the intervention area.
18
RESEARCH STATEMENT
As shown in the literature review, adverse clinical and nursing outcomes have
been investigated by a number of researchers in the last three decades. One of the primary
recommendation for ensuring patient safety identified by the Institute of Medicine (1999)
was instilling a safety culture within each individual organization. The perceived lack of
a robust safety culture has dire consequences in healthcare, with reported deaths from
medical errors ranging from 100,000 – 200,000 deaths per year from medical errors
(Underwood, 2004). In their landmark report, To Err Is Human (1999), the Institute of
Medicine has emphasized building a better relationships between physicians, nurses and
administrative executives in order to develop a robust safety culture.
Another threat to patient safety and organizational safety culture is identified as
physiological and psychological stress of RNs due to workplace incivility and disruptive
behaviors (Vessey, 2010). Psychological impacts, including stress, frustration, fear,
anxiety, depression, and loss of concentration have been reported in response to
disruptive behavior (McKenna et al., 2003; Rosenstein, 2005; Vessey et al., 2010).
Physical impacts of workplace incivility include inability to sleep, headaches, increased
blood pressure, weight loss, abdominal pain and gastrointestinal upset (Dumont et al.,
2012; McKenna et al., 2003; Vessey et al., 2010).
The Workplace incivility and
disruptive behavior have also been associated with decreased nursing satisfaction (
(Rosenstein & O'Daniel, 2005), quality of care (Purpora, 2010) and decreased nurse
productivity (Hutton & Gates, 2008). Disruptive behaviors promote nurses intent to leave
the organization (Sofield & Salmon, 2003; Johnson & Rea, 2009).
19
Because of the significant impacts on the psychological and physical well-being
of nurses, as well as the secondary consequences to patients and health care
organizations, it is imperative that effective means be identified to assuage workplace
incivility, foster healthy work environments, and cultivate true cultures of safety. In
terms of targeting disruptive behavior and other flawed communication as sources of
error, greater potential exists for interventions that target interactions among health care
team members by fundamentally altering an organization's culture for the better. This
study aims to contribute to this effort by investigating the nature of RN-MD relationship
norms and the impact of these relationship norms on nursing and clinical outcomes. This
study uses the methods of SNT to explore the gaps between the descriptive and injunctive
relationship norms of the RNs and the MDs. This study also explores the actual and
perceived norms regarding physicians’ behaviors and attempted to identify any
misperceptions among the RNs and the MDs, if existed (i.e. gaps between actual and
perceived norms).
Research Question and Conceptual Model
Most of the previous studies have consulted nurses to measure their perception of
workplace incivility, disruptive behavior and its impact on nursing satisfaction or clinical
outcomes. While few have surveyed the physicians’ perceptions regarding the same
issue. What is missing from these various research streams is a common study that will
measure the injunctive and descriptive norms of physicians and nurses regarding their
relationship culture. It is also important to measure the gaps between the perceived norms
20
of the RNs’ and the MDs’ as well as the actual norms regarding the relationship culture.
Social norms theory offers a helpful approach to study these norms and to find any gaps
among them.
This study used SNT to survey the physicians and the nurses of a specific area
(Montana and Denver) in order to explore the gaps between different norms and their
impact. The general research questions investigated by this study were –
•
Can a data collection instrument be built that measures the descriptive and
injunctive norms of the RNs and the MDs in a valid way?
•
Are there any differences in the descriptive and injunctive norms within
any of the populations regarding the RN-MD relationship culture?
•
Are there any differences in the actual and perceived norms within any of
the population regarding o The nature of the RN-MD relationship culture?
o The impact of the RN-MD relationship culture on nursing
outcomes and clinical outcomes?
In order to answer these questions, this study followed the conceptual model as
demonstrated in Figure 2. For the purpose of this study, overall cultural norms of the RNMD
relationship
was
divided
into
two
main
components
–
(1)
the
Interpersonal/Collaboration norms of physicians and nurses, and (2) the behavioral norms
(i.e. how the physicians behave toward the nurses). The elements of Component 1 were
taken from the findings of Schmalenberg and Kramer (2009). They identified 5 different
types of collaboration or relationship that may exist between physicians and nurses.
21
Component 2, the behaviors of physicians toward nurses, was divided into two subcategories, supportive physician behaviors (SPB) and disruptive physician behaviors
(DPB).
This study aimed to examine the impact of RN-MD relationship norms from two
aspects – the nursing impacts and the clinical impacts. Thus, the outcomes or impacts of
the RN-MD relationship culture were devided into these two parts – (1) nursing
outcomes, e.g. job satisfaction, retention and frustration/motivation of nurses and (2)
clinical outcomes, e.g. perceived medical error, delays in care. A data collection
instrument was developed to measure the descriptive and injunctive norms of RNs and
MDs regarding each element of RN-MD relationship culture as outlined in Figure 2.
Figure 2: Conceptual Model of Study
22
This study also aimed to address another gap identified in the literature review.
None of the previous studies have distinguished among the actual and perceived norms of
the RNs and the MDs regarding the RN-MD relationship culture and its impact on
clinical/nursing outcomes. The data collection instrument of this study measured the
actual and perceived relationship norms of the RNs and the MDs as illustrated in Figure
3. This study further explored the impact of the physicians’ behavior (i.e. behavioral
norms) on nursing and clinical outcomes. In order to explore this impact, the study
measured the actual opinion of each individual and their perception of their coworkers’
opinions as illustrated in the top half of Figure 3. The instrument development section
discused the design of questionnaire to explore actual and perceived norms of RNs and
MDs.
Figure 3: Overview of Cross-Evaluation Strategy of Different Relationship Norms
The collection and analysis of data in this study will allow for answers to the
following hypothesis:
23
1. H0: Statistical analysis provides evidence that the data collection instrument
cannot measure the cultural norms of RNs and MDs.
H1: The data collection instrument will measure the relationship norms of RNs
and MDs
2. H0: There is no difference between actual and perceived norms of RNs or
MDs regarding their relationship culture.
H1: There are differences between actual and perceived norms (i.e. vertical
and horizontal arrows within a box in Figure 3).
3. H0: There is no difference between the descriptive and the injunctive norms of
RNs or MDs regarding their relationship culture.
H1: There are differences between descriptive and injunctive norms of RNs
and MDs (i.e. vertical green arrows between boxes in Figure 3).
4. H0: There is no difference between the actual and perceived norms of RNs or
MDs regarding the impact of physicians’ behaviors on nursing outcomes.
H1: There are differences between actual and perceived norms of RNs or MDs
regarding the impact of physicians’ behaviors on nursing outcomes (i.e.
vertical and horizontal arrows within a box in Figure 3).
5. H0: There is no difference between actual and perceived norms of RNs or
MDs regarding the impact of physicians’ behaviors on clinical outcomes.
H1: There are differences between actual and perceived norms of RNs or MDs
regarding the impact of physicians’ behaviors on clinical outcomes (i.e.
vertical and horizontal arrows within a box in Figure 3).
24
Rationale and Contribution
From the literature review, it can be concluded that high quality nurse-physician
relationships are an important factor for nursing job satisfaction and quality of patient
care. Besides, interpersonal difficulties or communication gaps may create an adverse
patient condition (IOM, 1999). Although a number of studies have examined the nature
of these relationships, they have not distinguished between actual and perceived
relationship norms of RNs and MDs. Instead they have mostly focused on exploring the
presence/level of (perceived) disruptive physician behaviors, factors affecting these
behaviors and the ‘perception’ of nurses and physicians regarding the impacts of nursephysician relationship on clinical outcomes (i.e. medical error, quality of care etc.) and
nursing outcomes (i.e. retention, satisfaction etc.). In addition, the participants of these
studies were mostly nurses and rarely physicians. Thus the pictures of RN-MD
relationship culture that these studies have explored fall short of portraying both side of
the story. Besides, as the studies have mostly focused on investigating the ‘perception’ of
nurses (and physicians in few cases) and have not compared the ‘perception’ with the
‘actual experience’ of individual participants, the findings may not correctly represent the
relationship culture and its impact on clinical/nursing outcomes.
Since the perceptions of others’ behaviors are quite frequently inaccurate, with
views of problematic behaviors tending to be overestimated and healthy, protective
behaviors tending to be underestimated, a phenomenon known as “pluralistic ignorance”
(as cited by Berkowitz, 2005). The literature review section has shown the evidence that
overestimations and misperceptions have been identified within high school
25
popopulations (Hansen & Graham, 1991), adolescents in middle schools (Perkins, Craig,
& Perkins, 2011), pregnant women (Dunnagan et al., 2007) and statewide populations of
young adults (Linkenbach 1999, Linkenbach & Perkins 2003). These findings suggest the
possibility that a misperception may exist among the population of RNs and MDs
regarding the their relationship culture, disruptive behaviors and its impact on
clinical/nursing outcomes. Physicians may behave uncivil because it is mistakenly
assumed that such behavior is commonplace and accepted. In contrast, some behavior
may be overrated or believed to be overly common; but in reality, they are rarely
practiced. For example, physicians were to blame for a large part of disruptive behaviors
to nurses in clinical environment (Clinical Rounds, 2010), though the reasons for
disruptive behaviors were multi-factorial and include workload, nursing shortage,
organizational culture, and administration.
Social norms theory offers an innovative approach for addressing such situations
by changing perceptions and modifying beliefs (PCN Overview 2012, Dunnagan et al.
2007). The social norms theory suggests that people tend to behave in the way they
believe is most typical of and accepted by their peers, that is the perceived norms
(Berkowitz, 2005). It further predicts that individuals will alter their behavior for the
better when misconceptions are corrected and true norms revealed. In order to reduce
medical error and other negative clinical and organizational outcomes associated with
incivility and disruptive behavior, as in-depth understanding of descriptive and injunctive
behavioral norms as both experienced and perceived by both the physicians and the
nurses is required. Efforts should be initiated to investigate if any misperception exists.
26
This study aimed to explore if any misperception exists by investigating the gaps
among the descriptive and injunctive norms of RNs and MDs. This study explores what
the participants actually think and what they perceive of their coworkers; opinion
regarding RN-MD relationship norms and their impact. This approach enables
identification of any misperceptions exists among the population. If any misperception or
overestimation is found, then it would create a window to improve the relationship
culture by changing the perceptions and modifying the beliefs through application of
SNT. Additionally, the findings should provide a more complete understanding of the
relationship culture which is expected to be useful in designing a cultural intervention
program. A successful intervention program is expected to improve workplace
environment which will lead, in long run, into increased job satisfaction of nurses and
reduced adverse clinical outcomes.
27
METHODOLOGY
The purpose of this study is to explore the descriptive and injunctive norms of the
nurse-physician relationship culture. In addition, this study aims to examine the impact of
this relationship culture on clinical and nursing outcomes.
Instrument Design and Rationale
A number of studies have examined the nature of nurse, physician relationship
culture, presence of disruptive behaviors and their impact on nursing and clinical
outcomes. Almost all the studies used the survey method of different types – interview,
paper-and-pencil etc. For the purpose of this study, a quantitative, descriptive and crosssectional design sample survey method was developed to evaluate the relationship culture
and its impact on clinical and nursing outcomes.
Two separate survey instruments were designed to collect inputs of physicians
and nurses. Although the instruments of the RNs and the MDs were separate, the contents
and objectives of each element in both instruments were very similar. This enabled a
comparison between the responses of the RNs and the MDs. The development of the
instruments followed the conceptual model illustrated by Figure 2. The first part of the
instrument focused on exploring the interpersonal/collaboration norms of the RNs and the
MDs. This part included questions regarding the five types of RN-MD relationship as
outlined by Schmalenberg & Kramer (2009). Schmalenberg and Kramer surveyed over
20,000 nurses and identified that there were five types of relationship between the
28
physicians and the nurses – (1) Collegial, (2) Collaborative, (3) Student-Teacher, (4)
Friendly-Stranger and (5) Hostile/adversarial type relationship.
Schmalenberg and Kramer (2009) characterized collegial relationship by ‘equal’
power, trust and respect, and collaborative relationship by ‘mutual’ power, trust and
respect. For collaborative relationship, cooperation was considered based on ‘mutuality’
rather than ‘equality’. In a collaborative relationship, nurses and physicians listen to each
other but nurses feel that physician are always in a superior role. Student-teacher is a
relationship type where both the physicians and the nurses could teach and learn from
each other willingly. The friendly stranger relationship is characterized by a formal
exchange of information and a somewhat neutral feeling tone (Schmalenberg & Kramer,
2009). A situation where physicians come in, check on the patients and leave, and the
nurse speak after they are questioned by the physician may be a good example of
friendly-stranger relationship. Hostile/adversarial relationship between physicians and
nurses is characterized by anger, frustration, power play, domination. In this relationship,
nurses would feel frustrated or being domineered by the interaction with physicians.
A total of 10 questions, 2 questions addressing each of the five relationship types,
were initially developed. However, as the study used social norms theory, a questionnaire
was necessary to address both descriptive and injunctive norms. As illustrated in Figure
1, both the descriptive and the injunctive norms have two components – actual norms and
perceived norms. Thus, the 10 questions were expanded to address all 4 aspects of the
relationship norms, i.e. actual descriptive norms, perceived descriptive norms, actual
29
injunctive norms and perceived injunctive norms. So, total of 40 questions were obtained
addressing interpersonal/collaboration norms of the RN-MD relationship type.
The second part of the instrument focused on exploring the behavioral norms of
the RN-MD relationship (Figure 2), in other words, how the physicians behave toward
nurses. These behaviors were divided into two sub-categories – supportive physician
behaviors and disruptive physician behaviors. In the literature review, previous works
that investigated the RN-MD relationship have focused mostly on different components
regarding disruptive behaviors and excluded the positive behaviors. So initially four
disruptive behaviors were selected for this study from the Nursing Incivility Scale
(Guidroz et al., 2010) and the Workplace Incivility Scale – Revised (Cortina, et al.,
2011). These four behaviors were selected because their presence was found in nonmedical (Cortina, et al., 2011) and medical environments (Sirota 2008, Guidroz et al.
2010, Rosenstein & O'Daniel 2005, Rossenstein, Russell, & Lauve 2002, Rossenstein
2002). These behaviors were – (1) abusive behavior, (2) shouting or yelling if nurses
make mistakes, (3) taking feelings out on nurses and (4) not responding in a timely
manner. After selecting disruptive physician behaviors (DPB), four supportive physician
behaviors (SPB) were selected to contrast with the DPB. They were – (1) cooperative
behavior, (2) correcting nurses in a supportive way if they make a mistake, (3) acting
supportive if nurses are stressed or frustrated and (4) Responsive to nurses’ concerns in a
timely manner. The reason of this selection was to see how the SPB and the DPB that
were similar but opposite impacted nursing and clinical outcomes. Unlike the first section
(interpersonal norms), behavioral norms aimed to explore the descriptive norms and did
30
not capture injunctive norms. So each question was modified to address the actual and the
perceived descriptive norms (i.e. how the individual nurses experience and how the
nurses perceived that other nurses experienced these behaviors from physicians)
The third section of the instrument development focused on exploring the actual
and perceived impact of DPB and SPB on nursing and clinical outcomes. Five negative
and five positive outcomes were selected for DPB and SPB respectively. The negative
outcomes were - (1) increase delays in care, (2) increases incidence of medical error, (3)
increase frustration, (4) decrease job satisfaction and (5) increase intent to leave the job.
The positive outcomes were opposite and in contrast to the negative outcomes. They were
– (1) reduce delays in care, (2) reduce incidence of medical error, (3) increase motivation,
(4) increase job satisfaction and (5) increase commitment toward job. Here, questions 1
and 2 addressed the clinical outcomes and Question 3 to 5 addressed the nursing
outcomes. Each questioned were then modified to address the actual impact and
perceived impact.
In order to develop the physicians’ instrument, similar questions were used,
modified to reflect the physicians’ part of view. For example, physicians were asked how
frequently they had demonstrated any particular behavior. The instrument also included
demographic questions regarding age, gender, years of experience, nature of work
location (rural/urban etc.) and the unit of work (e.g. pediatrics, critical care unit etc.).
Rationale for Selecting Survey Method:
Survey is a remarkably useful and efficient tool for learning people’s opinion and
behaviors. The characteristics of millions of people can be estimated with confidence by
31
collecting information from only a few hundred or thousand respondents selected
randomly from carefully defined populations (Dillman, Smyth, & Christian, 2009). A
descriptive design research approach provides helpful information about frequency of
occurrence and ‘average’ beliefs and behaviors of target population (Schaefer, 2004). A
quantitative design research approach allows for establishing connections among
different measures that are being explored. This study aims to collect data on behavioral
norms and the belief and observations of physicians and nurses regarding their
relationship culture and the impact of that culture on perceived clinical outcomes and
nursing outcomes. Thus a survey method that is designed in a descriptive, quantitative
and cross-sectional style gives an appropriate way of pursuing this study objective.
Validation of the Instrument
Dillman, Smyth, and Christian (2009) recommended pretesting an instrument to
validate the readability, usability and applicability of the survey. For the purpose of this
study, a two-phase validation was conducted prior to surveying the intended population.
In the first phase, a group of subject matter expert reviewed the instruments. This phase
aimed to identify bias, readability and applicability of the questions. This step identified
the necessity of capturing supportive physician behaviors and the impact of these
behaviors on nursing and clinical outcomes. In the second phase, a test-survey was
conducted with a sample of nursing students from Montana State University. This phase
aimed at identifying the probable issues regarding interpretations or difficulty in
understanding the questions by the participants. The student survey found a few issues
32
regarding the instructions and readability. The instrument was reviewed and modified
according to the findings of the validation process.
Experiment Setting and Subjects
The primary target population of this study were physicians and nurses working in
different healthcare organizations of urban and rural Montana. The accessible population
of actively licensed in-state nurses was 12,146 and the accessible population of actively
licensed, in-state physicians was 2628 as of October 30, 2013 (MT.gov, 2013). In order
to enable future work to conduct cultural comparisons among urban and rural locations,
this study also surveyed the Denver, CO area which is somewhat demographically similar
to the State of Montana, and retains many traits of western and mountain state culture and
yet is also distinctively urban. This sampling frame consists of all licensed MDs and
licensed RNs from the three most highly populated counties in Denver metropolitan area
(i.e. Arapahoe, Denver and Jefferson counties). Based on the assumption that healthcare
providers living in metropolitan area would also work in the metropolitan area, an
accessible population of 13,884 actively licensed RNs and 5,554 actively licensed MDs
were found in the urban Denver area as of October 30, 2013.
Sampling Strategy
According to the probability sampling method (Dillman, Smyth, & Christian,
2009, p. 56), it is the sample size that affects the precision, not the portion of population.
The combined available population of the RNs from Montana and Denver, CO area was
26,030 (MT.gov, 2013) as on October 30, 2013. For 95% confidence interval and 5%
33
margin of error, a sample size of 379 was necessary for this study (SurveySystem, 2013).
Total available population of the MDs from the State of Montana and Denver, CO area
was 8182 as of October 30, 2013. For a 95% confidence level and 5% margin of error, a
required sample size was 367 (SurveySystem, 2013). Since not everyone returns the
completed survey in any paper and pencil survey, over sampling becomes necessary for
a quality survey.
From previous behavioral survey works on nurses and residents of Montana gave
different response rates. For example, Addison (2012) conducted a survey on nurses of
five large Montana hospitals regarding their perception of disruptive behaviors. She used
the hospitals intranet (with permission of management) to communicate with 120 nurses
and observed a response rate of 47.5%. In contrast, Schaefer (2004) conducted a random
paper and pencil survey with the residents of Montana’s Anaconda Deer Lodge County
(ADLC) regarding their perceptions for medical out-shopping and observed a 32.8%
response rate. Another similar survey on ADLC residents regarding their knowledge
about scope of practice for nurse practitioners, Connors (2000) performed a random
sampling of the ADLC population and generated a 25% survey return rate. Stout (2012),
on the other hand, conducted a study on Pediatric Dentists of Washington, Oregon, Idaho,
Utah and Montana regarding their willingness to participate in practice based research.
He emailed the survey to 293 pediatric dentists (who had verified email address) and
observed 76 completed responses after 6 weeks (25%). He mailed the hard copy of the
survey to 217 pediatric dentists who did not respond to email survey and observed 77
34
completed mailed survey return in 12 weeks (35.5%). This study gave a contrast of
response rate between email based survey and paper-pencil survey.
Though Addison (2012) reported an encouraging response rate (47.5%), she used
an electronic survey through hospitals’ intranet and the total number of response was 57
(out of 120). However, for the purpose of this survey, getting willingness of hospital
authority to participate in the survey might not be possible in most cases. This survey
involved both the RNs and the MDs and asked information related to the behavioral
norms. Thus, it might raise concern regarding conflict of interest for the organizations.
Emailing the target participants to their personal email could be another option for
electronic survey. But Stout’s (2012) work identified a lower response rate through
emailed/online survey compared to paper-pencil survey. Additionally, email addresses of
licensees are unavailable via the professional licensing boards in Montana and Colorado.
Considering these challenges regarding electronic survey, a paper and pencil survey
method was selected for this study. The survey questionnaire was mailed directly to the
physical mail of each target participants. Regarding response rate, paper and pencil
survey of Schaefer (2004) and Connors (2000) was considered as a better match to the
current work. Thus a response rate of 30% to 35% was expected from this paper and
pencil survey, i.e. the survey was necessary to mail around 1185 RNs and 1147 MDs
considering 32% response rate. Finally, the survey was mailed to 1220 nurses and 1129
physicians.
This survey aimed to identify perceive and actual norms of both physicians and
RNs regarding nurse-physician relationship culture. Participation was thus very important
35
and non-response bias was a threat to validity. Evidence suggested that a small incentive
offered in advance not only enhanced the return rate, but specifically reduced non
response bias by compelling individuals who otherwise might not have answered the
questionnaire to complete it (Dillman, Smyth, & Christian, 2009). Unfortunately,
university policy prohibited the cash offer enclosed with the surveys and thus a ‘gift
voucher’ incentive program was selected to enhance response rate. A fair lottery program
was developed and offered to the survey recipient. Table 3 gives an outline of the lottery
incentive program that was used for this study.
Table 3: Proposed outline lottery incentive program
Number of Winners
Lottery Money
1
$500
21 to 60
2
$300 each
61 to 100
2
$200 each
101 to 200
5
$100 each
Every 100 respondents 201+
Up to 10
$100 each
Post Marked Response
First 1 to 20
Data Collection
At first, a list of physical addresses of target physicians and nurses working at
both urban and rural Montana location was obtained. Then a similar list of target
physicians and RNs of urban Denver counties (as mentioned above) was obtained. A
random sample was selected from these lists and a set of questionnaire was mailed to
them. In addition to the questionnaire, the mailing package included a letter explaining
the purpose of the survey, and the incentive offering, pre-addressed, stamped envelope to
36
facilitate survey return and a contact card to participate in the prize drawing. The target
participants were selected randomly. A return survey implied consent to participate. All
documents were printed on MSU letterhead.
The recipients were given a fixed date as a deadline to return their response. Five
days before the deadline, a reminder card was sent to each participant requesting them to
submit the survey if they had not done yet. The reminding card also included the online
address of the survey in case the participants had lost the original copy of the instrument.
Contact cards with personal information submitted by those wishing to be entered into
the lottery drawing were separated upon receipt to assure no responded could be linked to
any questionnaire. The deadline was extended with the reminder card to increase the
response. The data were then entered into an Excel file.
Data Analysis Plan
The data analysis was conducted in three different sections using Microsoft Excel
and Minitab-16 to examine the five hypothesis outlined in the methodology section. The
first hypothesis aimed to evaluate the ability of the data collection instrument to measure
the norms of RN and MD in a valid way. Cluster analysis, factor analysis and item
analysis were performed with the data sets to examine this objective. The reason of
selecting each of these analysis techniques were explained in corresponding data analysis
section.
Hypotheses 2, and 3 focused on investigating if there was any gaps between either
actual and perceived norms or descriptive and injunctive norms of the RN-MD
relationship culture. Two proportion test and 2-sample t-test were conducted for each of
37
the relevant items of the instrument to evaluate these hypotheses. Hypothesis 4 and 5
focused on investigating the gaps of actual and perceived norms regarding the impact of
physicians’ behavior on nursing and clinical outcomes respectively. Two proportion test
and 2-sample t-test were conducted for each of the relevant items of the instrument to
evaluate these hypotheses.
Ethics and Protection of Human Subjects
Montana State University Institutional Review Board (IRB) reviewed the study in
Fall-2013 and approved it in the exempt category (Approval in Appendix B). No personal
information that could identify the participants were collected as a part of main body of
survey. However, for the purpose of the cash lottery, interested participants were asked to
provide their address and phone number. This identification information was removed
immediately from the survey upon receipt. The cover letter included in the survey packet
explained that participation in the survey would be voluntary and that completing and
returning the survey provided the consent of respondent.
38
DATA ANALYSIS AND RESULTS
The survey was mailed to total of 2349 participants. Among them, 138 packets
were returned as ‘undelivered’. A total of 510 of the target participants responded to the
survey; among them, 20 respondent reported as ‘retired’ or ‘not engaged in practice in
last 12 months’ and their surveys were not included. Table 4 demonstrates the detail
statistics of the survey mail and response status of this study. Among the 490 remaining
participants, 461 responded to all (85) the questions, 14 participants responded to 84
questions, 2 participants responded to 83 questions, 5 responded to 79 to 82 questions and
the remaining 8 participants responded to only 52 to 67 questions. For consistency of data
analysis, the 482 responses who responded at least 79 questions were selected for data
analysis and the remaining 8 responses were disregarded.
Table 4: Statistics of Survey Mail and Responses
Montana RNs
Mailed
Out
746
Montana MDs
670
19
651
130
19.97%
126
Colorado RNs
474
33
441
76
17.23%
73
Colorado MDs
459
22
437
60
13.73%
60
Not applicable
-
-
-
20
-
2349
138
2211
510
23.07%
TOTALS
224
%
Response
32.84%
Response
Accepted
223
Returned
Net Mailing
Responded
64
682
482
Demographic Analysis of the Study Data Sets
The full data collection process was completed with populations of two different
areas – the State of Montana State and Denver, Colorado. Among the 482 responses
39
selected for the analysis, 133 respondents (27.6%) were from Denver and the additional
349 respondents (72.4%) were from the State of Montana. A total of 296 respondents
(61%) identified themselves as RN and 186 respondents (39%) identified themselves as
MD. Figure 4 demonstrates the participants’ demographic information analysis by
different criteria. Appendix C describes the details of demographic information analysis.
A significant number of respondents (34%) characterized their primary work
setting as ‘Others’ (Figure 4). Further analysis of their responses identified more than
fifty (50) different work settings including mental health, radiology, family physician,
homecare, genetics, public health, ambulance care, infusion center, physical therapy,
clinic research, rehab and so on. Some respondents identified two or three different units
as their primary work setting. However, only one response was counted for the analysis.
Data Analysis
As described previously, the data analysis was conducted to evaluate each of the
hypothesis separately. The first hypothesis aimed to evaluate the ability of the data
collection instrument to measure the norms of RN and MD in a valid way. Cluster
Analysis (CA), Factor Analysis (FA) and Item Analysis were performed with the data
sets to examine this hypothesis. Hypotheses 2 to 5 stated that there was no difference
between the descriptive and injunctive norms as well as actual and perceived norms
regarding the relationship norms of the physicians and the nurses. Two sample t-test and
two proportions test were performed to evaluate these hypotheses.
40
Participants by Area
Participants by Gender
CO RN
15%
MT MD
26%
CO MD
13%
Preferred
not to
answer
Male
3%
29%
CO RN
Female
68%
CO MD
MT RN
46%
Preferred
not to
answer
1%
50+ Years
47%
MT RN
Male
MT MD
Preferred not to
answer
Participants by Age
20 - 30
Years
8%
31 - 40
Years
23%
Partipants by Job Location
Rural
12%
20 - 30 Years
41 - 50 Years
Small
Town
30%
50+ Years
Preferred not to
answer
20+ Years
47%
Urban
3-5
Years
10%
2 Years
or less
6%
6 - 10
Years
13%
11 - 15
Years
16 - 20
14%
Years
8%
Urban
41%
Suburban
Small Town
Rural
Suburban
14%
Not Sure
Participants by Work
Department
Participants by Experiences
Preferred
not to
answer
2%
Not Sure
3%
31 - 40 Years
41 - 50
Years
21%
Female
Medical/
Surgical
Unit
23%
Others
34%
Emerge
cy
9%
OR/post
Pediatrics
Anesthesi
6%
a
8%
Figure 4: Demographic Summary
CCU
9%
Obstetric
Administrs/Gynoco
logy
ation
7%
4%
41
For standard t-test ANOVA and other parametric tests like factor analysis,
structure equation model, hierarchical linear model and so on, it is the assumption of
normality of the distribution of means, not of the data (Norman, 2010). The Central Limit
Theorem shows that, for sample sizes greater than 5 or 10 per group, the means are
approximately normally distributed regardless of the original distribution (Norman,
2010). The sample size of this study is 482 (RN - 296, MD – 196), which is significantly
higher and indicates that the mean would be normally distributed. In addition, normality
test was performed with the mean response of participants following Anderson-Darling
method of Minitab 16. The p value for RN and MD data sets (i.e. mean) were found
0.414 and 0.257 respectively [See Appendix D]. This p value suggested that the data
means followed normal distribution.
Examination of Hypothesis 1
Hypothesis 1 stated that the statistical analysis would provide evidence that the
data collection instrument could not measure the relationship norms of RNs and MDs. In
order to examine this hypothesis, several parametric tests have been performed. At first,
cluster analysis (Anderson et al. 2010, Stevens 2002, Johnson & Wichern 2002,
Anderson 1984) was used to evaluate the natural groupings within the data. The
components of each cluster were then compared with the designed groups of the
instrument to explore logical relationship among them. Item analysis was then performed
on each cluster to evaluate the internal consistency. After performing cluster analysis,
factor analysis was conducted using Principal components method. For the purpose of
this report, only the findings of CA were discussed and the findings of FA were
42
illustrated in appendix E. Note that both of the analyses provided supporting evidence to
reject hypothesis - 1.
Cluster analysis (CA) were selected because it was the appropriate interdependent
multivariate analytical techniques to find an underlying structure to the entire set of
variables or subjects (Anderson et al., 2010). In general, clustering of variables is used to
classify variables into groups when the groups are initially unknown (Anderson , 1984).
CA alse selected if the cases or respondents are to be grouped to represent structure
(Anderson et al., 2010). For the purpose of this study, CA was selected for several
reasons. First, the dependency of the variables were not completely known and thus
interdependent multivariate analytical techniques were the appropriate tool for the
analysis. CA is an interdependent multivariate analytical technique. Second, the data
collection instrument measures several cases. For example, different relationship nature,
supportive and disruptive physician behaviors, impact of these behaviors on nursing and
clinical outcomes. The CA was thus an appropriate tool to analyze the data in order to
find the groups and to compare the groups (as explored by CA) with the design groups of
the data collection instruments. If the clusters reflect logical similarities with the
constructed groups of the instrument and the components within each cluster are found
internally consistent, then it will be the evidence to reject null hypothesis, in other words,
the instrument measured the relationship norms of RN and MDs in a valid and reliable
way.
Cluster analysis was completed by entering the raw responses (integer value 1 -5)
into Minitab 16. Data sets of RN and MD were analyzed separately due to the differences
43
between the instruments and the purpose of Item Analysis for further exploration of
clusters. For Item Analysis in Minitab 16, the number of rows in each column must be
same. But the number of data for RN and MD of this study are not same.
At first, single linkage method with similarity target of 0.7 was used for the
analysis due to its simplicity (Johnson & Wichern, 2002). Appendix E demonstrates the
dendrogram obtained from this analysis. As illustrated by it, this method of cluster
analysis was not found useful in identifying major clusters in the data sets. Thus, further
cluster analysis was conducted using Ward’s method. The Ward’s method of cluster
analysis was used for its ability to minimize the ‘loss of information’ of joining groups
through weighting the clusters (Johnson & Wichern, 2002, p. 690). Using an unrestrained
analysis setting, this method generated a set of Eight (8) clusters. Here, all eight clusters
contain logically similar questions within same group. Q 01-10 and Q 02-10 were
expected to be grouped with Q 01-9 and Q 02-9 as they were designed to reflect ‘Formal
Relationship’ nature. This unexpected inclusion of Q 01-10 and Q 02-10 with the group
of questions regarding disruptive behavior (Q09 and Q11) indicates that nurses consider
this particular behavior stated in Q 01-10 as more similar to being disruptive instead of
formal in nature. Table 5 provides a quick overview of the clusters and comments on
similarities.
In order to further understand the internal consistency of the data sets within each
clusters, item analysis was performed using Minitab 16. Item Analysis evaluated how
reliably multiple items in a survey measures the same construct by presenting several
types of statistics. One of them is Cronbach's alpha that measures the degree of internal
44
consistency for all included items (Anderson 1984, Cronbach 1951). The associated
Cronbach’s Alpha value of each clusters was displayed in Table 5. All of the components
exceeded the general rule of a desired internal consistency of 0.70 or above (Cronbach,
2004) except for Cluster 6. The Cronbach’s alpha value for Cluster 5 was 0.6633 which is
very close to 0.7 and can be considered significant. Besides, the Item-Adj.-Total
Correlation and the Squared-Multiple Correlation value for each of the items of cluster 6
were significantly higher.
Similar cluster analysis was performed with MD data sets. This analysis produced
10 clusters. Appendix E demonstrates the findings of this cluster analysis and comments
on the similarities of components of each cluster. Item analysis explored Cronbach’s
Alpha value above 0.7 for all the clusters except for cluster 9 (i.e. 0.5074). The lower
Cronbach’s alpha value for this cluster suggests a lack of consistency within the items as
a single construct. Further look into the cluster gives a possible explanation. Cluster 9
includes 4 questions – Q09-1 to Q09-4. All 4 questions asked the physicians regarding
how frequently they demonstrated mentioned disruptive behaviors. Q09-1 and Q09-2
asked about being verbally abusive to nurses and shouting at them if they make a
mistake. Q09-3 and Q09-4 asked about taking feelings of frustration, stress or anger out
on RN and not responding their concern timely. Clearly, there are strong differences
regarding the intensity of disruptiveness of Q09-1, 2 and Q09-3, 4. The responses of MD
reflects this differences as well. For example, 170 and 176 MDs (out of 186) responded
‘never’ to Q09-1 and Q09-2 respectively. In contrast, 104 and 76 MDs responded ‘never’
to Q09-3 and Q09-4 respectively. Besides, though the 4 questions were in same cluster,
45
there were two sub-clusters with different similarity level as demonstrated by the
dendrogram (See Appendix E).
Table 5: Clusters of RN Data Sets and associated Cronbach's Alpha value
Clusters
Cluster 1
Q 01-1 Q 01-2
Q 02-1 Q 02-2
Q 05-1 Q 05-2
Q 07-1 Q 07-2
Comments
Descriptive norms of positive
type behavior (both actual and
perceived)
0.9120
Collegial Relationship (All
Norms)
0.8134
Cluster 3
Q 01-6 Q 01-9 Q 02-6 Q 02-9
Q 03-6 Q 03-9 Q 04-6 Q 04-9
Q 03-10 Q 04-10
Collaborative & Formal type of
behaviors – both descriptive
and injunctive norms
0.8048
Cluster 4
Q 01-7 Q 01-8
Q 02-7 Q 02-8
Q 09-1 Q 09-2
Q 11-1 Q 11-2
Negative/disruptive Type of
behaviors (Descriptive)
0.8964
Cluster 5
Q 03-1 Q 03-2 Q 03-3 Q 03-4
Q 04-1 Q 04-2 Q 04-3 Q 04-4
Injunctive norms regarding
positive behaviors
0.8683
Cluster 6
Q 03-7 Q 03-8 Q 04-7 Q 04-8
Negative behaviors (Injunctive)
0.6633
Cluster 7
Q 06-1 Q 06-2 Q 06-3 Q 06-4 Q 06-5 Q
08-1 Q 08-2 Q 08-3 Q 08-4 Q 08-5
Impact of supportive behaviors
(Actual and Perceived)
0.9417
Cluster 8
Q 10-1 Q 10-2 Q 10-3 Q 10-4 Q 10-5 Q
12-1 Q 12-2 Q 12-3 Q 12-4 Q 12-5
Impact of disruptive behaviors
(Actual and Perceived)
0.9124
Cluster 2
Q 01-5 Q 02-5
Q 01-3
Q 02-3
Q 05-3
Q 07-3
Q 01-4
Q 02-4
Q 05-4
Q 07-4
Cronbach’s
Alpha value
Q 03-5 Q 04-5
Q 01-10
Q 02-10
Q 09-3 Q 09-4
Q 11-3 Q 11-4
The clusters identified for RN data sets were very similar but not completely
identical to the clusters identified by MD data sets. One of the reasons of getting some
46
differences in the clusters for RN and MD data sets could be the difference in the norms
of RNs and MDs. Further analysis discussed later in this chapter supported this reason.
However, regardless of their differences, many similarities were also observed among
them. Appendix E includes a table that demonstrated the similarities of different clusters
of RN and MD using variety of colors. For example, cluster 7 of RN data sets included
both the actual and perceived norms of the impact of supportive physician behaviors. For
MD data sets, actual norms and perceived norms were grouped into two clusters (cluster
7 and 8).
Conclusion of Cluster Analysis: The finding of cluster analysis for both RN and
MD data sets were logical, reasonable and in most cases, reflected the constructed groups
of the data collection instruments within same clusters. The Cronbach’s alpha value for
all the clusters and factors were found substantially higher. These findings provide
evidence that the data collection instrument was able to measure the relationship norms
of RNs and MDs in a valid and reliable way, in other words, these findings reject the null
hypothesis of hypothesis 1.
Hypothesis 2 – Actual vs Perceived
Norms of Relationship Culture
As described in the methodology, the instrument addressed the relationship norms
and its impact on nursing and clinical outcomes. The relationship norms were divided
into two sections – interpersonal/collaboration norms (Q01 – Q04) and the behavioral
norms (Q05, Q07, Q09 and Q11) of the RNs and the MDs. The following sections
analyzed the difference among the actual and perceived relationship norms of RNs and
47
MDs. Questions of each section were analyzed individually using 2-sample t-test
(Stevens, 2002). In addition, each type of responses (i.e. agree-disagree or never-always)
were also cross-examined using two proportions hypothesis test (Stevens, 2002). All the
tests were conducted using Minitab 16.
Hypothesis 2 – Actual vs Perceived Descriptive Norms (Interpersonal): To
illustrate how the analysis was conducted and compared among different norms, analysis
of Q01-1 has been described below. Question 01-1 asked the participants regarding how
often the physicians were willing to explain issues related to patient care to nurses. In this
question, RNs reported their own experiences (with MDs behaviors) and MDs reported
their own behaviors (toward nurses). Figure 5 to Figure 8 demonstrate the percentage (%)
of responses of RN and MD. Table 6 demonstrates the results of statistical analysis of
their responses. For example, Figure 5 demonstrates the actual norms reported by the
RNs and the MDs. Here, 76% of the RNs responded ‘usually’ to ‘always’, whereas 99%
MDs reported ‘usually’ to ‘always’. This differences were found statistically significant
in two-proportion test at 95% CI (p value 0.00). A two-sample t-test was conducted on
the overall actual norms of RNs and MDs (Q 01-1) and significant difference was found
among their norms (p value 0.00). MD reported of demonstrating ‘willingness to explain’
behaviors more frequently than the RNs actually experienced (Table 6). Similarly, actual
and perceived norms of RNs and MDs were analyzed and cross-examined for each
relationship type (Q01 and Q02).
48
Physician as Teacher - Actual vs Perceived
Norms of RN (Q 01-1 vs Q 02-1)
Relationship Norms of MD and RN Physician as Teacher (Q 01-1)
74%
80%
56%
60%
40%
17%
20%
1%0%
6%
0%
25%
20%
1%
0%
60%
50%
40%
30%
20%
10%
0%
Never Seldom About Usually Always
Half the
RN MD
time
Figure 5: Physicians as teacher - Actual
Norms of RN and MD
74%
61%
60%
30% 25%
40%
20%
0%0%
0%3%
1%
7%
0%
48%
35%
20%
17%
1%0%
Never
6% 8%
Seldom
8%
About Usually Always
Half the
RN Actual
time
RN Perceived
Figure 6: Physician as Teacher - Actual vs
Perceived Norms of RN (Q 01-1 vs Q 021)
Physician as Teacher - Actual vs Perceived
Norms of MD (Q 01-1 vs Q 02-1)
80%
56%
Physicians as Teacher - Perceived Norms
of RN and MD (Q 02-1)
70%
60%
50%
40%
30%
20%
10%
0%
61%
48%
35%
30%
8%
0%0%
3%
8% 7%
Never Seldom About Usually Always
Half the
MD Actual
time
MD Perceived
Never Seldom About Usually Always
Half the
RN Perceived
time
MD Perceived
Figure 7: Physician as Teacher - Actual vs
Perceived Norms of MD (Q 01-1 vs Q 02-1)
Figure 8: Physicians as Teacher Perceived Norms of RN and MD (Q 02-1)
Table 6: Results on 'Physician as Teacher' (Q01-1: Physicians are willing to explain issues regarding patient care to nurses)
% Response
Two-proportions test (CI 95%)
1%
Seldom
About
Half the
time
Usually
6%
8%
0%
3%
0.408
-
0.000
0.006
17%
35%
1%
30%
0.000
0
0.000
0.200
56%
48%
25%
61%
0.083
0
0.000
0.008
Always
20%
8%
74%
7%
0.000
0
0.000
0.725
RN Actual
(RN Q01-1)
MD Actual
(MD Q01-1)
MD Perceived
(MD Q02-1)
RN Q01-1 vs
RN Q02-1
0%
0%
1.000
MD Q01-1
vs MD Q021
-
RN Q01-1 vs
MD Q01-1
RN Q02-1 vs
MD Q02-1
0.156
0.316
Two-Sample t-test (CI 95%)
RN Q01-1 vs RN Q02-1
MD Q01-1 vs MD Q02-1
RN Q01-1 vs MD Q01-1
RN Q02-1 vs MD Q02-1
Not equal
(p value 0.0)
RN Q01-1 > RN Q02-1
Not equal
(p value 0.0)
MD Q01-1 > MD Q02-1
Not equal
(p value 0.0)
RN Q01-1 < MD Q01-1
Not equal
(p value 0.006)
RN Q02-1 < MD Q02-1
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
49
Never
RN
Perceived
(RN Q02-1)
0%
Response
Type
50
Appendix F1 contains the results of this analysis for each questions of this section
(Descriptive Norms). From these tables, it was evident that nurses received positive
behaviors from physicians more frequently than they perceived other nurses have
received them in past 12 months (Q01-1 to Q01-5). Similar results were observed for
physicians as well, that is, physicians responded demonstrating positive behavior more
frequently but they perceived most other MDs would demonstrate these behaviors less
frequently than themselves (except for Q01-2 which was equal).
Table 7 summarizes the outcome of this analysis. The signs indicate the findings
of hypothesis 2 for respective question. Equal (=) sign indicates fail to reject the null
hypothesis, reject otherwise. It can also be observed from the table that the RNs’ actual
and perceived norms were either ‘less frequent’ or equal when compared to physicians’
respective norms for these questions. This suggests that physicians believe they behave
better than nurses think they do. The opposite results were obtained for the questions that
were negative in nature (Table 7). These results clearly indicate significant gaps between
the actual and perceived descriptive norms of the RNs and the MDs in most aspects of
their interpersonal relationship culture. In other word, null hypothesis was found to be
rejected for all the norms that were not equal in Table 7, otherwise fail to accept H0.
Table 8 demonstrates the percentage of participants reported ‘usually to always’
for five questions (positive relationship) and ‘never to seldom’ to the remaining five
questions (negative relationship) of this section. The difference between the actual and
perceived norms (i.e. misperceptions) among the RNs and the MDs are well illustrated
from this table.
51
Table 7: Results of Hypothesis 2 (Descriptive Norms)
Actual vs Perceived Interpersonal Relationship
Norms (Descriptive)
Interpersonal Norms (Relationship type)
Question
#
MDs willing to explain (MD as teacher)
Nurses influence MD (MD as student)
Appropriate authority (Collegial)
Readily available (Collegial)
Develop care plan together (Collaborative)
Physicians decide care plan (Collaborative)
Frustrated by interaction (Hostile)
Physicians act domineering ( Hostile)
Formal interaction (Formal)
RN role to answer question (Formal)
Q 01-1
Q 01-2
Q 01-3
Q 01-5
Q 01-4
Q 01-6
Q 01-7
Q 01-8
Q 01-9
Q 01-10
RN Actual
vs RN
Perceived
>
>
>
>
>
=
<
<
=
<
MD Actual
vs MD
Perceived
>
=
>
>
>
>
<
<
<
<
RN Actual
vs MD
Actual
<
=
<
<
<
<
>
>
>
>
Table 8: Actual vs Perceived Interpersonal Norms - % of Selected Response
RN
Actual
RN
Perceived
MD
Actual
MD
Perceived
% of participants responded Usually
to Always
% of participants responded Never to
Seldom
Q011
Q012
Q013
Q014
Q016
Q015
Q017
Q018
Q019
Q0110
76%
54%
71%
44%
49%
32%
72%
71%
30%
43%
56%
41%
51%
30%
53%
42%
43%
52%
28%
29%
99%
46%
94%
61%
90%
4%
96%
97%
52%
78%
68%
42%
57%
25%
85%
29%
59%
54%
25%
36%
Hypothesis 2 - Actual vs Perceived Injunctive Norms (Interpersonal): The
differences between the perceived and actual injunctive norms of the RNs and the MDs
were analyzed using the 2-proportions test and two sample t-tests. Appendix F2 contains
the results of this analysis for each of the questions of this section (i.e. Injunctive Norms).
52
Table 9 summarizes the findings of this section from two sample t-test. These results
indicate the presence of significant gaps between actual and perceived injunctive norms
of some aspects of RN-MD relationship nature (Interpersonal/Collaboration norms). In
other words, hypothesis 2 was found to be rejected for all the norms that were not equal
in Table 9, otherwise fail to reject H0. Table 10 demonstrates the percentage of
participants reported agree to positive type relationship and disagree to negative type of
relationship culture.
Table 9: Results of Hypothesis 2 (Injunctive Norms)
Actual vs Perceived Norms (Injunctive)
Interpersonal Norms (Relationship type)
Question
MDs willing to explain (MD as teacher)
Nurses influence MD (MD as student)
Appropriate authority (Collegial)
Readily available (Collegial)
Develop care plan together (Collaborative)
Physicians decide care plan (Collaborative)
Frustrated by interaction (Hostile)
Physicians act domineering ( Hostile)
Formal interaction (Formal)
RN role to answer question (Formal)
Q 03-1
Q 03-2
Q 03-3
Q 03-5
Q 03-4
Q 03-6
Q 03-7
Q 03-8
Q 03-9
Q 03-10
RN Actual
vs RN
Perceived
=
=
=
=
>
=
=
=
=
=
MD Actual
vs MD
Perceived
>
>
>
>
>
=
<
<
<
<
RN Actual
vs MD
Actual
=
>
>
=
>
<
=
=
=
<
Table 10: Injunctive norms of RN and MDs - % of selected responses
% of participants responded 'agree to
strongly agree'
RN
Actual
RN
Perceived
MD
Actual
MD
Perceived
% of participants responded 'disagree to
strongly disagree'
Q03-1
Q03-2
Q03-3
Q03-4
Q03-5
Q03-6
Q03-7
Q03-8
Q03-9
Q03-10
98%
93%
96%
96%
69%
44%
99%
98%
51%
84%
98%
95%
95%
91%
70%
43%
99%
99%
56%
79%
99%
90%
92%
83%
78%
9%
98%
97%
46%
80%
91%
65%
76%
54%
58%
5%
94%
90%
28%
51%
53
Hypothesis 2 – Actual vs Perceived Behavioral Norms (SPB): Table 11 displays
the summary of findings from the two-sample t-test of supportive physician behaviors
(Q05 vs Q07). For supportive physician behaviors, actual norms of RNs and MDs were
found statistically greater than of respective perceived norms, that is, the RNs
experienced supportive behaviors from more physicians than they perceived of what
other RNs had experienced. Similarly, the MDs demonstrated supportive behaviors more
frequently than they perceived of what other the MDs had experienced. Similar to
previous sections, both the actual and perceived norms of the RNs were smaller than the
MDs’ respective norms. Appendix F3 demonstrates the detail results of the two sample ttest and the 2-proportions test of this sections. This section also reflects the presence of
statistically significant differences among the norms of the RNs and the MDs in all the
aspects of supportive physician behaviors. In other words, hypothesis 2 was found to be
rejected for all the norms that were not equal in Table 11, otherwise fail to reject H0.
Table 12 demonstrates the percentage of participants reported ‘most to everyone’ (for
RNs) or ‘usually to always’ (for MDs) regarding each of the questions addressed
supportive physician behaviors. This table illustrates the misperceptions among
physicians and nurses regarding supportive physician behaviors.
54
Table 11: Results of Hypothesis 2 (SPB)
Actual vs Perceived Norms (Supportive Physician Behavior)
Supportive physician
behaviors (SPB)
Question
#
RN Actual vs
RN Perceived
MD Actual vs
MD Perceived
RN Actual vs
MD Actual
Cooperative behavior
Correct supportively
Act supportive if stressed
Responsive timely
Q 05-1
Q 05-2
Q 05-3
Q 05-4
>
>
>
>
>
>
>
>
<
<
<
<
Table 12: SPB - % of selected responses
% of participants
Cooperative
Behaviors
Correct
supportively
Act supportive
if stressed
Responsive
timely
Q 05-1
Q 05-2
Q 05-3
Q 05-4
RN Actual (most to everyone)
90%
65%
50%
68%
RN Perceived (most to everyone)
63%
44%
36%
48%
MD Actual (usually to always)
100%
91%
91%
95%
MD Perceived (usually to always)
80%
56%
53%
66%
Participant (Response type)
Hypothesis 2 – Actual vs Perceived Behavioral Norms (DPB): Table 13 displays
the summary of findings of two sample t-test of disruptive physician behaviors and its
impact on nursing and clinical outcomes. The findings were opposite to the findings of
previous section (supportive behaviors). This section demonstrates the presence of
statistically significant gaps among the norms of RNs and MDs in different aspects of
disruptive physician behaviors. In other words, hypothesis 2 was found to be rejected for
all the norms that were not equal in Table 13, otherwise fail to reject H0. Detail results of
this section were captured from in Appendix F4. Table 14 demonstrates the percentage of
participants reported never (MD data sets) or none (RN data sets) regarding disruptive
55
physicians behaviors. This table illustrates the misperceptions among physicians and
nurses regarding disruptive physician behaviors.
Table 13: Results of Hypothesis 2 (DPB)
Actual vs Perceived Norms
Disruptive physician
behaviors (DPB)
Question #
RN Actual vs
RN Perceived
MD Actual vs
MD Perceived
RN Actual vs
MD Actual
Abusive behavior
Shouting
Take feelings out
Not responding timely
Q 09-1
Q 09-2
Q 09-3
Q 09-4
<
<
<
<
<
<
<
<
>
>
>
>
Table 14: DPB - % of selected responses
Participants
(Response type)
RN Actual (None)
RN Perceived (None)
MD Actual (Never)
MD Perceived (Never)
% of participants reported Never (MD) or None (RN)
Abusive
Take
Not responding
Shouting
behavior
feelings out
timely
Q 09-1
Q 09-2
Q 09-3
Q 09-4
74%
76%
50%
31%
26%
26%
18%
12%
91%
95%
56%
41%
23%
26%
14%
7%
Summary of Results for Hypothesis 2: From the above analysis, hypothesis 2 was
found to be rejected for both the interpersonal/collaboration norms and the behavioral
norms. The evidences provided by the two sample t-test and two-proportion test
supported that misperceptions existed among the nurses and the physicians. Supportive
behaviors and positive interpersonal norms were perceived to be less frequently displayed
than the actual norms. In contrast, disruptive behaviors and negative interpersonal norms
were reported to be perceived more frequently displayed than the respective actual
56
norms. In summary, statistically significant gaps were found among actual and perceived
norms of the nurses and the physicians.
Hypothesis 3 – Descriptive
vs Injunctive Norms (Interpersonal)
Two sample t-test and two proportions test were applied to RN and MD data sets
to explore hypothesis 3, i.e. if there is any gap between the descriptive norms and
injunctive norms between RN (and MD). Table 15 summarizes the findings from the two
sample t-test. Appendix F2 demonstrates the detail findings of this analysis. From Table
15, it is evident that the descriptive and injunctive norms of RN were not same for any of
the question. In other words, hypothesis 3 was found to be rejected for all the norms that
were not equal in Table 15, otherwise fail to reject H0. For first five questions that were
positive in nature (equal or mutual power), descriptive norms were smaller than that of
injunctive norms, i.e. RNs believed that their relationship to MDs should have been more
collegial, collaborative and student-teacher type in nature than they experienced past 12
months. For the next five questions that were negative in nature, descriptive norms were
greater than of injunctive norms, i.e. RNs believed that their relationship should not as
formal or hostile in nature as they experienced in past 12 months.
57
Table 15: Results of Hypothesis 3 (Descriptive vs Injunctive Norms)
MDs willing to explain (MD as teacher)
Q 01-1
RN Actual-D
vs RN Actual-I
<
Nurses influence MD (MD as student)
Q 01-2
<
<
Appropriate authority (Collegial)
Q 01-3
<
=
Readily available (Collegial)
Q 01-5
<
=
Develop care plan together (Collaborative)
Q 01-4
<
<
Physicians decide care plan (Collaborative)
Q 01-6
>
>
Frustrated by interaction (Hostile)
Q 01-7
>
>
Physicians act domineering ( Hostile)
Q 01-8
>
>
Formal interaction (Formal)
Q 01-9
>
=
RN role to answer question (Formal)
Q 01-10
>
=
Relationship Type
Question
MD Actual-D vs
MD Actual-I
=
Hypothesis 4 – Impact of
Behavioral Norms on Nursing Outcomes
The RNs were given a set of supportive physician behaviors (SPB) and disruptive
physician behaviors (DPB), and asked how those behaviors had impacted their job
satisfaction, motivation and intent to leave the profession, if physicians had demonstrated
them. They were also about their perception of other RNs opinion regarding the effect of
those behaviors. Similarly, the MDs were given the same set of SPB and DPB, and were
asked how those behaviors impacted the RNs, if they had demonstrated them. They were
also asked about their perception of other MDs opinion regarding the effect of those
behaviors. Then the respective norms of the RNs and the MDs were compared using two
sample t-test and two-proportions test. Table 16 demonstrates the findings of two-sample
t-test. Hypothesis 4 was found to be rejected for all the norms that were not equal in
Table 16, otherwise fail to reject H0. Detail results of this section were captured in
Appendix F3 and Appendix F4.
58
Table 17 demonstrates the percentage of participants responded ‘agree to strongly
agree’ regarding the impact of SPB and DPB on nursing outcomes.
Table 16: Results of hypothesis 4 (Impact on Nursing Outcomes)
Actual vs Perceived Norms (Supportive Physician Behavior)
Impact of SPB on
increasing Motivation toward job
Job Satisfaction
Commitment
Question #
Q 06-3
Q 06-4
Q 06-5
RN Actual vs
RN Perceived
=
>
=
MD Actual vs
MD Perceived
>
>
>
RN Actual vs
MD Actual
=
=
=
Actual vs Perceived Norms (Disruptive Physician Behavior)
Impact of DPB on
increasing Frustration
Job Dissatisfaction
Intent to leave
Question #
Q 10-3
Q 10-4
Q 10-5
RN Actual vs
RN Perceived
<
<
MD Actual vs
MD Perceived
=
=
RN Actual vs
MD Actual
>
=
Table 17: Impact of physician behavior on nursing outcomes
Impact of Supportive Physician
Behaviors
RN
Actual
RN
Perceived
MD
Actual
MD
Perceived
Impact of Disruptive Physician
Behaviors
Motivation
Satisfaction
Commitment
Frustration
Dissatisfaction
Intent to
leave
Q 06-3
Q 06-4
Q 06-5
Q 10-3
Q 10-4
Q 10-5
85%
88%
86%
84%
73%
61%
83%
84%
81%
92%
89%
80%
89%
91%
84%
76%
74%
60%
74%
71%
67%
80%
75%
64%
Hypothesis 5 – Impact of
Behavioral Norms on Clinical Outcomes
Similar to the previous section, respective norms of the RNs and the MDs
regarding the impact of SPB and DPB were explored and compared to investigate if there
59
was any difference between actual and perceived norms. Table 18 demonstrates the
findings of two-sample t-test. Hypothesis 4 was found to be rejected for all the norms that
were not equal in Table 18, otherwise fail to reject H0. Detail results of this section were
captured in Appendix F3 and Appendix F4.
Table 19 demonstrates the percentage of participants responded ‘agree to strongly
agree’ regarding the impact of SPB and DPB on clinical outcomes.
Table 17: Results of hypothesis 5 (Impact on Clinical Outcomes)
Actual vs Perceived Norms (Supportive Physician Behavior)
Impact of SPB on
reducing -
Question
#
RN Actual vs
RN Perceived
MD Actual vs
MD Perceived
RN Actual vs
MD Actual
Delays in Care
Q 06-1
=
>
<
Medical Error
Q 06-2
=
>
<
Actual vs Perceived Norms (Disruptive Physician Behavior)
Impact of DPB on
increasing Delays in Care
Question
#
Q 10-1
RN Actual vs
RN Perceived
<
MD Actual vs
MD Perceived
=
RN Actual vs
MD Actual
>
Medical Error
Q 10-2
<
=
=
Table 18: Impact of physician behavior on perceived clinical outcomes
RN Actual
RN Perceived
MD Actual
MD Perceived
Impact of SPB
Reduces Delays
Reduces
in Care
Medical Error
Q 06-1
Q 06-2
84%
77%
82%
77%
88%
90%
78%
75%
Impact of DPB
Increases
Increases
Delays in Care
Medical Error
Q 10-1
Q 10-2
74%
53%
84%
70%
56%
49%
58%
52%
60
Additional Findings
This study also enabled the researchers to investigate additional questions
regarding nurse-physician relationship culture, and its effect on nursing and clinical
outcomes. This section aimed to answer the following additional questions:
•
Do physicians display supportive behaviors or disruptive behaviors toward
nurses?
•
Do physician behaviors have any effect on nursing outcomes (i.e. job
satisfaction, retention etc.)
•
Do physician behaviors have any effect on perceived clinical outcomes
(i.e. delays in care, medical errors etc.)
The hypotheses used to answer these questions were –
6. H0: Physicians do not display supportive behaviors toward the nurses.
H1: Physicians display supportive behaviors toward the nurses.
7. H0: Physicians do not display disruptive behaviors toward the nurses.
H1: Physicians display disruptive behaviors toward the nurses.
8. H0: Physicians’ behaviors have no effect on nursing outcomes.
H1: Physicians’ behaviors have significant effect on nursing outcomes.
9. H0: Physicians’ behaviors have no effect on clinical outcomes.
H1: Physicians’ behaviors have significant effect on clinical outcomes.
A 1-sample t-test was used to examine these hypotheses. For the questions with
response type ‘agree-disagree’, one sided hypothesis tests were performed against target
61
mean 3, i.e. neither disagree nor agree. Thus, a p-value less than 0.05 indicated rejection
of null hypotheses.
Do Physicians Display
Supportive Behaviors Toward Nurses?
The nurses were presented with examples of supportive physician behaviors
(SPB) and were asked how many physicians displayed those behaviors to them. They
were also asked about their perceptions of other nurses’ response regarding these same
questions. The response type for these questions were none (1), few (2), some (3), most
(4) and everyone (5).
The physicians were presented with the same examples of supportive behaviors
and were asked how frequently they demonstrated those behaviors toward nurses.
Physicians were also asked about their perceptions of other physicians’ behaviors
regarding the same questions. The responses for these questions were never (1), seldom
(2), about half the time (3), usually (4) and always (5).
In order to examine this hypothesis, 1-sample t-test was performed against target
sample mean 3 (i.e. ‘some’ for RN data sets and ‘about half the time’ for MD data sets).
For all the questions, null hypothesis was found to be rejected for the actual and
perceived response of the RNs and the MDs (See Appendix G). That is, both the
physicians and the nurses reported that the physicians displayed supportive behaviors
toward nurses. Figure 9 demonstrates the percentage of RNs who reported ‘most’ to
‘everyone’ of physicians displayed supportive behaviors toward nurses. For example,
90% of the RNs reported ‘most-to-all’ physicians displayed cooperative behaviors toward
themselves, whereas they perceived only 63% of the RNs would report that most-to-all
62
physicians displayed cooperative behaviors toward nurses. Figure 10 demonstrates the
percentage of MDs who reported ‘usually to always’ regarding how frequently physicians
demonstrated supportive behaviors toward nurses. Similar to RN data sets, gaps were
observed among the actual and perceived norms of the physicians.
Figure 9: % of RNs reported 'most' to 'everyone'
of MDs displayed SPB
Figure 10: % of MDs reported 'Usually' to
'Always' regarding displaying SPB
Do Physicians Display
Disruptive Behaviors Toward Nurses?
Similar to previous section, physician disruptive behaviors were also examined
using 1 sample t-test against target sample mean 1 (i.e. none for RN data sets and Never
for MD data sets). . Null hypothesis was found to be rejected for all the questions
regarding disruptive physician behaviors. That is, physicians displayed disruptive
behaviors as reported by nurses and self-reported by physicians.
In addition to above findings, percentage of RNs who reported ‘none’ to number
of physicians displayed disruptive behaviors were examined and illustrated in Figure 11.
63
For example, three in every four RNs reported that ‘no physician’ had displayed ‘abusive
behaviors’ toward them, whereas only one in every four RNs reported that they perceived
physicians had displayed ‘disruptive behaviors’ toward other nurses. Similar
misperceptions were observed among the physicians (Figure 12).
Figure 11: % of RNs reported 'No Physician'
displayed disruptive behaviors
Figure 12: % of MDs reported 'Never'
regarding displaying DPB
Effects of Physicians
Behaviors on Nursing Outcomes
After presenting the supportive behaviors and disruptive behaviors by physicians,
the RNs and the MDs were asked if those behaviors had any effect on nursing outcomes.
They were also asked about their perceptions of coworkers’ opinion regarding these same
questions. The responses were collected using a 5 – point Likert type scale of Strongly
Disagree (1) to Strongly Agree (5). Initially, 1-sample t-test was conducted against the
target mean 3 (Neutral). A sample mean greater than 3 in 1-sample t-test would indicate
64
agree, i.e. physicians behaviors do have impact on nursing outcomes. Appendix G
demonstrates the detail findings of this analysis. According to this analysis, null
hypothesis of hypothesis was found to be rejected for all questions of RN and MD data
sets. That is, both the physicians and the RNs reported that SPB positively impacted the
nursing outcomes and DPB adversely impacted the nursing outcomes.
Effects of Physicians
Behaviors on Clinical Outcomes
Similar to previous section, effect of physicians’ behaviors on perceived clinical
outcomes were examined. The response type for this section was a 5-point Likert type
scale – strongly disagree (1) to strongly agree (5). Appendix G demonstrates the findings
of this analysis. Null hypothesis of hypothesis 9 was found to be rejected for all the
questions. That is, both the physicians and the RNs reported that they thought SPB
positively impacted the clinical outcomes and DPB adversely impacted the clinical
outcomes.
65
CONCLUSION AND DISCUSSION
The intent of this study was to investigate the nature of relationship culture
between physicians and nurses, and the impact of this relationship culture on nursing
outcomes and perceived medical errors. The necessity of this study was indicated by a
review of the literature. This review found extensive influence of different components of
RN-MD relationship culture on nursing outcomes and the quality of patient care
(Rosenstein & O'Daniel 2005, Rossenstein 2002, Schmalenberg & Kramer 2009,
Addison 2012, Dumont et al. 2012, Johnson & Kring 2012, McKenna et al. 2003). But
almost all of these previous studies investigated the perceived relationship norms and its
impact as reported by mostly the nurses. There was not a single study that had aimed to
investigate both the actual and perceived norms of RN and MD regarding their
relationship norms and how it might impact nursing and patient outcomes. In addition, no
other study was found that investigated the descriptive and injunctive norms of RN and
MD in this regard. This study aimed to address this this gap and the findings of this study
would contribute to better understand the norms of the RNs and the MDs regarding these
aspects.
In order to make a contribution, a two part study was necessary. One of the
reasons that no previous study had examined the gaps between the actual and perceived
norms of RN-MD relationship culture, is that no reliable instrument to explore the norms
existed. In addition, no tool existed to unfold the impact of relationship norms on nursing
and clinical outcomes. Therefore, the first part of the study was the development of a new
instrument to measure this cultural and behavioral norms and their impacts. The second
66
part was to conduct a survey of RN and MD in order to explore these norms and their
impacts. The responses of the survey participants were examined to look for differences
in norms of RNs and MDs. These findings provided statistical support to make decisions
on the hypotheses formulated in the study.
Hypothesis Testing Results and Contribution
The study investigated five separate hypotheses. The first hypothesis examined
whether the instrument could measure the relationship norms or RN and MD in a valid
way. This hypothesis was necessary to validate the instrument and explore lack of
internal consistency within the instrument construct. This hypothesis was –
H0:
Statistical analysis provides evidence that the data collection instrument
cannot measure the cultural norms of RNs and MDs in a valid way
H1:
Data collection instrument can measure the cultural norms of RNs and
MDs.
The analysis of the data collected from the responses of participants suggested to
reject the null hypothesis for both of the instruments of the RNs and the MDs. This
rejection was accomplished through cluster analysis (Anderson et al. 2010, Stevens 2002,
Johnson and Wichern 2002, Anderson 1984) and item analysis (Stevens 2002, Anderson
1984) using Minitab 16.
The cluster analysis of the RN data sets identified eight clusters. Each of the
clusters included logically similar questions as designed by the instrument. The clusters
identified by this analysis were then validated by the item analysis. Item Analysis
evaluates how reliably multiple items in a survey measures the same construct by
67
presenting several types of statistics (Anderson 1984, Cronbach 1951). Here, Cronbach's
alpha value that measured the degree of internal consistency was used to determine the
reliability of the clusters (Cronbach 2004, 1951). This analysis resulted in significant
Cronbach’s alpha value (over 0.7) for each of the clusters. In addition, factor analysis
(Anderson et al. 2010, Stevens 2002) was also conducted to examine hypothesis 1 and the
outcomes substantiated the findings of cluster analysis (see Appendix E).
The second hypothesis investigated the gaps between the actual and perceived
relationship norms of RN and MD. This hypothesis stated that –
H0:
There is no difference between actual and perceived norms of any
population groups.
H1:
There are differences between actual and perceived norms of at least one
population group.
The analysis of data collected to evaluate this hypothesis rejected the null. The
rejection of this hypothesis was accomplished by two sample t-test and two proportions
test using Minitab 16. The two proportions test evaluated the responses of each pair of
contrasting questions. The two sample t-test explored the gap from overall responses of
each pair of contrasting questions. Though the actual norms and the perceived norms
were found to be the same for a few aspects of the relationship culture, the overall norms
were not found to be the same for either RNs or MDs. Additionally, significant gaps were
identified among the actual norms as well as the perceived norms of the RNs and the
MDs (i.e. between the two groups)
68
The third hypothesis examined the gaps between the descriptive norms and
injunctive norms of RN and MD. This hypothesis stated that –
H0:
There is no difference between descriptive and injunctive norms of any
population groups.
H1:
There are differences between descriptive and injunctive norms of at least
one population group.
The analysis of data collected to evaluate this hypothesis rejected the null for both
RN data sets and MD data sets. This rejection of hypothesis 3 was accomplished by two
sample t-test (Stevens 2002) and two proportions test (Stevens 2002). The descriptive and
injunctive norms were found different for all the components of RN-MD relationship
culture. For MD data sets, descriptive and injunctive norms were found same for five
components and different for rest five components.
The fourth hypothesis examined the gaps between the actual and perceived norms
of the RNs and the MDs regarding the impact of physicians’ behaviors on nursing
outcomes, i.e. job satisfaction, intent to leave, motivation/frustration. The hypothesis
states H0: There is no difference between the actual and perceived norms of the RNs or
the MDs regarding the impact of physicians’ behaviors on nursing outcomes.
H1: There are differences between actual and perceived norms of the RNs or the
MDs regarding the impact of physicians’ behaviors on nursing outcomes.
The analysis rejected null hypothesis for both RN and MD data sets for supportive
physician behaviors (SPB) and disruptive physician behaviors (DPB). The actual and
69
perceived norms were found not same for many components of the impact of physicians’
behaviors on nursing outcomes
The fifth hypothesis examined the gaps between the actual and perceived norms
of the RNs and the MDs regarding the impact of physicians’ behaviors on clinical
outcomes, i.e. perceived medical error, delays in care. The hypothesis states H0: There is no difference between the actual and perceived norms of the RNs or
the MDs regarding the impact of physicians’ behaviors on clinical outcomes.
H1: There are differences between actual and perceived norms of the RNs or the
MDs regarding the impact of physicians’ behaviors on clinical outcomes.
The analysis of data rejected the null hypothesis for MD data sets for SPB and
DPB. But it failed to reject null hypothesis for RN data sets regarding SPB, i.e. no
difference was found between the actual and perceived response of the RNs regarding the
impact of supportive physicians’ behaviors on clinical outcomes. However, the analysis
rejected null hypothesis for RN data sets regarding DPB.
Discussion and Theoretical Implications of the Study
The examples of reducing alcohol consumption in pregnant women and reducing
drinking and driving behavior demonstrated the significance of gaps between actual and
perceived norms (i.e. misperceptions) and its impact on unsafe behaviors. In this study,
several potential gaps among the actual norms and perceived norms were identified that
might have undesired behavioral consequences. For example, 74% of the RNs reported
that no physicians behaved abusive toward them. In contrast, only 26% of the RNs
reported that they perceived no physician behave abusive toward other nurses. In other
70
words, 1 out of every 4 RNs reported that physician displayed abusive toward them,
whereas 3 out of 4 RNs perceived that physicians displayed abusive toward other nurses.
This demonstrates a gap between actual and perceived norms of the RNs (i.e.
misperception). This misperception may have effect on nursing outcomes, i.e. job
satisfaction, intent to leave etc.
From the physician’s survey, 91% of the MDs reported that they ‘never’
displayed abusive behaviors toward the nurses. In contrast, only 23% of the MDs
reported that they perceived most other MDs ‘never’ display abusive behaviors toward
the RNs. In other words, 1 out of every 10 MDs reported of displaying disruptive
behaviors, whereas 8 out of 10 MDs perceived that most other physicians displayed
disruptive behaviors toward the nurses. This finding demonstrates a misperception among
the MDs. Similar misperceptions (with different magnitude) were identified for all four
questions that addressed the disruptive physician behaviors. This misperception may
enable the undesired behaviors of the MDs toward the RNs as suggested by the social
norms theory.
In addition, the findings of this study explored a perceived correlation between
physicians’ behaviors and nursing outcomes. Supportive physician behaviors were found
to be positively associated with increased motivation, job satisfaction and commitment of
nurses toward the profession as reported by both RNs and MDs. In contrast, disruptive
physician behaviors were found to be associate with increased frustration, job
dissatisfaction and turnover of nurses. This study also explored a perceived correlation
between physicians’ behaviors and clinical outcomes. Supportive physician behaviors
71
were found to be associated with reduced delays in care and medical errors as reported by
both RNs and MDs. In contrast, disruptive physician behaviors were found to be
associated with increased delays in care and medical error.
The findings of this study reinforce the need to address relationships and
behaviors as a fundamental component of safety culture in healthcare environment. The
findings also indicate significant misperceptions among the nurses and the physicians
regarding different components of their relationship culture. Thus an intervention
program based on SNT could prove effective in reducing these misperceptions.
Limitations of the Study
The study has limitations that may restrict the overall applicability of its findings.
First of all, the study was completed using a target population of RNs and MDs of
Montana and Denver, CO area. Denver, Colorado is somewhat demographically similar
to Montana State and retains many traits of western, mountain state culture and yet are
also distinctively urban. This would allow future study of comparing the relationship
norms between rural and urban area. This target population does not include significant
other areas of the country. Thus, the findings of this study may not reflect the relationship
norms of physicians and RNs of overall United States.
Second, this study does not fully consider influence of the specific work settings
of each participants within their respective professions. The way in which the RN role is
enacted may vary by their work setting, For example, the cultural norms of RNs or MDs
who work in emergency department may vary from the RNs or MDs who work in
gynecology or other departments. Nor does it address the specific role of each participant
72
within their respective setting. Nurses prepared as Advanced Practice Registered Nurses
(APRNs) may interact with physicians differently than nurses prepared at a more basic
level of practice. The data collection instrument collects the information about work
settings and other demographics, but the data analysis leaves these demographic aspects
out of scope of current thesis.
Third, the data sets utilized for the study was relatively small. The combined
available population of RN from the State of Montana and the metropolitan Denver areas
was 26,030. For 95% confidence interval and 5% margin of error, a sample size of 379
was necessary for this study (SurveySystem, 2013). The achieved number of responses
from RN was significantly lower (296). It increases the margin of error from 5% to
5.66% (SurveySystem, 2013). Similarly, for MD data sets, total number of available
population of the State of Montana and the metropolitan Denver areas was 8182. For a
95% confidence level and 5% margin of error, a required sample size was 367
(SurveySystem, 2013). The number of responses achieved for this study was significantly
lower as well (196). This increases the margin of error from 5% to 6.92%.
Fourth, this study collected the frequency of supportive behaviors and disruptive
behaviors as reported by the MDs themselves. For the descriptive norms, physicians selfreported their actual behaviors and their perceptions of other physicians’ actual
behaviors. The physicians may have reported less-frequent to the questions of undesirable
behaviors (disruptive) and high-frequent to the questions of desirable behaviors
(supportive) than their actual behaviors toward the nurses. Thus, the collected data may
have a biasness regarding undesirable (DPB) and desirable (SPB) behaviors.
73
Finally, a one directional relationship was assumed between disruptive/uncivil
behaviors and clinical outcomes (i.e. medical error, delays in care) in this study. But an
opposite directional relationship might be possible between uncivil behaviors and
undesirable clinical outcomes. For example, low performing units (e.g. high moral error)
may lead to low morale which cause the disruptive/uncivil behaviors. This study did not
consider this possibility. The respondents perceived that there was a relationship between
disruptive behaviors and adverse clinical outcomes.
Areas for Future Works and Recommendations
No other studies have attempted to investigate the relationship norms of RNs and
MDs by exploring both the actual and perceived norms nor the descriptive and the
injunctive norms. This study has demonstrated that relationship norms of RNs and MDs
are not identical. In addition, this study has also demonstrated that there are gaps between
the actual and perceived norms of RNs as well as of MDs. While demonstrating the
differences among the relationship norms, the study has raised additional questions. The
recommended areas for future study are as follows:
□
Exploration of cultural norms of other areas of the United States: As
discussed in the limitations, the target population for this study was the
State of Montana and the metropolitan Denver areas. In order to evaluate a
better perspective of a country-wide RN-MD relationship norms, the study
shall be reproduced in other areas of the United States. The study should
also be reproduced in some other parts of the world to evaluate the RN-
74
MD relationship norms. This global expansion could help to understand
and compare the RN-MD relationship norms of United States with other
countries.
□
Exploration of the Cultural Norms of Rural and Urban Area: The target
population for this study was the State of Montana and the metropolitan
Denver areas. This multi-population sample has opened a window to
perform further research in order to understand the differences between
the cultural norms of rural population when compared to urban
populations.
□
Further Exploration of the Impact of Different Work Settings: This study
collects data on the type of work settings of the participants, but does not
explore the differences in the relationship norms among the participants of
different work settings. The cultural norms of RNs and MDs who work in
emergency department may vary from the RNs and MDs who work in
gynecology or other departments. Further exploration of the impact of
different work settings on the cultural norms may help us in understanding
the changes in norms from one setting to another. It should also help to
identify which work settings require more attention while developing a
social intervention program.
□
Exploration of the Impact of Other Demographics on Cultural Norms:
This study also collects information of participants’ gender, age and years
of work experience. Further study is necessary to investigate if there is any
75
effect of these demographics on the cultural norms of RN-MD
relationship.
□
Exploration of the perceptions of hospital leaders: Many of the hospital
leaders are not directly involved in patient care but related to descriptive
and injunctive norms of behaviors among the RNs and the MDs. If
leadership is to be included in any subsequent interventions, it is
imperative that the perceptions of hospital leaders (not related to patient
care) are evaluated.
□
Replication of the study on additional medical professions – e.g. physical
therapy, respiratory therapy, etc.
□
Exploration of the perceived norms of nursing students and medical
students related to descriptive and injunctive norms regarding the RN-MD
behaviors.
□
As described in the limitations, the rotated factor analysis was unable to
significantly load many questions. Thus, a confirmatory factor analysis
may be used in future to get a better perspective regarding the ability of
data collection instruments to measure the relationship norms.
□
The response type for SPB and DPB was different for the instruments of
the RNs and the MDs. This differences hindered the comparison of the
norms of RNs and MDs. For the future study, same response pattern
should be used to collect the responses of both RNs and MDs. A revised
and recommended instrument has been attached in the Appendix.
76
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82
APPENDICES
83
APPENDIX A
DEFINITION OF KEY TERMS REGARDING SOCIAL NORMS THEORY
84
Actual Norms:
Actual norms, also known as social norms, are the behaviors or attitudes of the
majority of people in any community or group (PCN Overview, 2012). If most people in
a community do not drink, then not drinking is the ‘normative’ behavior, or the actual
norm. Not drinking is normal, acceptable, and perhaps even expected in that population.
Let’s consider Kathy is a registered nurse working in a hospital ‘X’. If she finds all the
physicians are cooperative to her, then ‘Physicians are cooperative’ is her actual norms.
The collection of this ‘actual norms’ (i.e. the collective actual experience) of all the
nurses of hospital ‘X’ is the ‘actual social norms’ of the RNs of that hospital.
Perceived Norms:
Perceived norms, also known as peer norms or perceptions of social norms, are
people’s beliefs about the norms of their peers. If a group of people think that most other
people drink and drive, then drink and drive would be their perceived norms. Consider
the example of Kathy – if she thinks that most physicians are not cooperative toward
other nurses, or if she thinks that most other nurses believe physicians are not cooperative
toward them, then ‘Physicians are not cooperative toward nurses’ is her ‘perceived
norms’.
Figure 13: Types of Norms and Their Inter-Connections
85
Descriptive and Injunctive Norms
Actual and perceived norms can be both descriptive and injunctive in nature.
Injunctive norms capture people’s attitudes, in particular, a sense of disapproval (“this is
wrong”) or an injunction (“should” or “should not”). Examples of injunctive norms are
‘most people think it is wrong to steal” or “most people believe they should exercise
regularly’ (PCN Overview, 2012).
In contrast, Descriptive norms describe the behaviors of people as opposed to
their attitudes. Examples of descriptive norms are ‘most people eat lunch every day’ or
‘most students do their homework’ (PCN Overview, 2012).
The examples of Kathy given above demonstrate descriptive norms. If Kathy
thinks that physicians should always be cooperative toward all nurses, then her actual
injunctive norms would ‘Physicians should always be cooperative toward nurses’. If
Kathy thinks that most other nurses believe that physicians should be cooperative towards
them when necessary, then her ‘perceived injunctive norms’ would be ‘Physicians should
be cooperative toward nurses as necessary’.
Significance of Perceptions
Perceptions of social norms play an extremely important role in shaping
individual behavior. People’s perception of what is acceptable, majority behavior — how
fast they think ‘most people’ drive, whether they think ‘most people’ wear seatbelts, how
many drinks they think ‘most people’ have before getting behind the wheel — play a
large role in our own behavioral decisions. Unfortunately, people often misperceive the
86
social norms of their peers, thinking that risky behavior occurs with far greater frequency
and social acceptance than it actually does (PCN Overview, 2012).
Misperceptions may have different forms and nature. Examples of most common
misperceptions found in any society are given below (Berkowitz, 2005):
•
Pluralistic Ignorance: Individuals may misperceive their social environments in
a number of ways that influence their behavior. For example, the majority who
engage in healthy behavior may incorrectly believe they are in the minority when
they are actually in the majority
•
False Consensus: In contrast to pluralistic ignorance, people may incorrectly
think that they are in the majority when they are actually in the minority.
•
False Uniqueness: An individual may enjoy thinking that his or her behavior is
more unique than it really is.
Non-Norms:
Non-norms are the behaviors or attitudes of the minority of people in any
community or group. Often people misperceive behaviors and believe they are norms
when in fact they are non-norms (PCN Overview, 2012).
87
Table 19: Example of Questions exploring Actual and Perceived Descriptive Norms
Nurses
Actual Based on your own experience of past 12
Descriptive months, how would you respond to the
Norms following statement –
Physicians
Based on your own experience of past
12 months, how would you respond to
the following statement –
‘Physicians are willing to explain issues
regarding patient care to me’
Perceived In your opinion, how would most other
Descriptive nurses in your workplace respond to the
Norms following statement –
‘I am willing to explain issues
regarding patient care to Nurses’
In your opinion, how would most other
physicians in your workplace respond
to the following statement –
‘Physicians are willing to explain issues
regarding patient care to nurses’
‘Physicians are willing to explain
issues regarding patient care to nurses’
Actual In past 12 months, how many physicians
Descriptive in your workplace have exhibited
Norms ‘Cooperative behaviors toward you’?
In the past 12 months, how frequently
have you exhibited ‘Cooperative
behavior toward nurses’
Perceived In your opinion, how would most other
Descriptive nurses respond regarding how many
Norms physicians exhibited ‘Cooperative
behaviors’ toward nurses?
In your opinion, how would most other
physicians respond regarding how
frequently they exhibited ‘Cooperative
behaviors’ toward nurses?
Table 20: Example of Questions Exploring Actual and Perceived Injunctive Norms
Nurses
Actual Based on your own experience as a RN,
Injunctive how would you respond to the following
Norms statement –
Physicians
Based on your own experience as a
MD, how would you respond to the
following statement –
‘Physicians should be willing to explain
issues regarding patient care to nurses.
Perceived In your opinion, how would most other
Injunctive nurses in your workplace respond to the
Norms following statement –
‘Physicians should be willing to explain
issues regarding patient care to nurses.
In your opinion, how would most other
physicians in your workplace respond
to the following statement –
‘Physicians should be willing to explain
issues regarding patient care to nurses
‘Physicians should be willing to explain
issues regarding patient care to nurses
88
APPENDIX B
APPROVAL OF INSTITUTIONAL REVIEW BOARD AND OTHER DOCUMENTS
89
90
91
APPENDIX C
DEMOGRAPHIC INFORMATION
92
Table 21: Participant Demographic Information by Gender
MT
MD
41
77
8
126
MT RN
Female
Male
Prefer not to Answer
Grand Total
Total by Area
203
16
4
223
Percent (%)
46%
20
38
2
60
Total
RN
265
24
7
296
Total
MD
61
115
10
186
Grand
Total
326
139
17
482
12%
61%
39%
100%
Total
MD
1
34
49
100
2
186
Grand
Total
37
113
103
224
5
482
39%
100%
CO RN
CO MD
62
8
3
73
349
133
26%
15%
Table 22: Participant Demographic Information by Age
MT RN
MT MD
CO RN
CO MD
20 - 30 Years
31 - 40 Years
41 - 50 Years
50+ Years
Prefer not to answer
Grand Total
23
61
42
95
2
223
1
24
32
68
1
126
13
18
12
29
1
73
0
10
17
32
1
60
Total
RN
36
79
54
124
3
296
Percent (%)
46%
26%
15%
12%
61%
Table 23: Participants Demographic Information by Experience
2 Years or less
3 - 5 Years
6 - 10 Years
11 - 15 Years
16 - 20 Years
20+ Years
Prefer not to
Grand Total
MT RN
MT MD
CO RN
CO MD
Total
RN
Total MD
Grand
Total
20
23
28
33
21
95
3
223
1
12
15
15
14
67
2
126
8
10
10
9
3
33
0
73
2
4
8
10
2
32
2
60
28
33
38
42
24
128
3
296
3
16
23
25
16
99
4
186
31
49
61
67
40
227
7
482
93
Table 24: Participant Demographic Information by Characteristics of Job Location
Urban
Suburban
Small Town
Rural
Not Sure
Grand Total
MT RN
MT MD
CO RN
CO MD
67
19
88
40
9
223
31
17
54
18
6
126
53
18
0
2
0
73
45
12
3
0
0
60
Total
RN
120
37
88
42
9
296
Total
MD
76
29
57
18
6
186
Grand
Total
196
66
145
60
15
482
%
41%
14%
30%
12%
3%
Table 25: Participant Demographic Information by Characteristics of Work Setting
Medical/Surgical Unit
Emergency
Obstetrics/Gynecology
Administration
CCU
OR/post Anesthesia
Pediatrics
Others
Grand Total
MT
RN
49
15
19
11
24
18
7
80
223
MT
MD
33
13
6
6
6
9
8
45
126
CO
RN
17
6
7
1
10
6
6
20
73
CO
MD
14
8
3
0
3
6
6
20
60
Total
RN
66
21
26
12
34
24
13
100
296
Total
MD
47
21
9
6
9
15
14
65
186
Grand
Total
113
42
35
18
43
39
27
165
482
%
23%
9%
7%
4%
9%
8%
6%
34%
100%
94
APPENDIX D
NORMALITY TEST OF STUDY DATA SETS
95
Normality test of RN Data Sets (Mean)
Normal
99.9
Mean
StDev
N
AD
P-Value
99
Percent
95
90
3.261
0.2289
296
0.374
0.414
80
70
60
50
40
30
20
10
5
1
0.1
2.50
2.75
3.00
3.25
3.50
Average_RN
3.75
4.00
Figure 14: Result of Normality Test of RN Data Sets using Anderson-Darling Method
Normality Test of MD Data Sets (Mean)
Normal
99.9
Mean
StDev
N
AD
P-Value
99
Percent
95
90
3.275
0.2151
186
0.461
0.257
80
70
60
50
40
30
20
10
5
1
0.1
2.50
2.75
3.00
3.25
3.50
Average_MD_1
3.75
4.00
4.25
Figure 15: Result of Normality Test of MD Data Sets using Anderson-Darling Method
96
APPENDIX E
CLUSTER ANALYSIS AND FACTOR ANALYSIS FOR HYPOTHESIS 1
97
EXAMINATION OF HYPOTHESIS - 1
Hypothesis 1 stated that the statistical analysis would provide evidence that the
data collection instrument could not measure the relationship norms of RNs and MDs. In
order to examine this hypothesis, several parametric tests have been performed. At first,
cluster analysis has been used to evaluate the natural groupings within the data. The
components of each cluster were then compared with the designed groups of the
instrument to explore logical relationship among them. Item analysis has also been
performed on each cluster to evaluate the internal consistency. After performing cluster
analysis, factor analysis has been conducted using Principal components method. This
analysis has enabled to explore significant factors and factor loading of each questions.
Result of factor analysis was then compared with the findings of cluster analysis.
Significant components of each factors were also compared with the designed groups of
the instrument to explore logical relationship among them. Both of the analysis will
provide supporting evidence for making decision about hypothesis - 1.
Factor analysis (FA) and cluster analysis (CA) were selected because they were
the appropriate interdependent multivariate analytical techniques to find an underlying
structure to the entire set of variables or subjects (Anderson et al., 2010). If the structure
of variables is to be analyzed, then factor analysis is the appropriate technique. If the
cases or respondents are to be grouped to represent structure, then cluster analysis is
selected (Anderson et al., 2010). Cluster analysis primarily groups objects, whereas factor
analysis focuses on grouping variables. For the purpose of this study, both CA and FA
were used for several reasons. First, the dependency of the variables were not completely
98
known and thus interdependent multivariate analytical techniques were the appropriate
tool for the analysis. Second, the data collection instrument measures several cases. For
example, different relationship nature, supportive and disruptive physician behaviors,
impact of these behaviors on nursing and clinical outcomes. The CA was thus an
appropriate tool to analyze the data in order to find the groups and to compare the groups
(as explored by CA) with the design groups of the data collection instruments. Third, in
addition to CA, factor analysis was also used to evaluate the structure of the variables and
their interrelationship (Afifi, May, & Clark, 2012). Comparing the findings of both CA
and FA would provide a robust understanding regarding the ability of data collection
instrument to evaluate the RN-MD relationship culture than any single technique.
Cluster Analysis
Cluster analysis is an analytical technique for developing meaningful subgroups
of objects. Cluster analysis is selected if the cases or the respondents are to be grouped to
represent structure (Anderson, Babin, Black, & Hair, 2010). For the purpose of this study,
at first the data sets were explored using cluster analysis (Johnson & Wichern, 2002) in
order to evaluate the natural groupings within the data and to compare the explored
groups with the designed groups of the instrument. This analysis was completed by
entering the raw responses (integer value 1 -5) into Minitab 16. Data sets of RN and MD
were analyzed separately due to the differences between the instruments and the purpose
of Item Analysis for further exploration of clusters. For Item Analysis in Minitab 16, the
number of rows in each column must be same. But the number of data for RN and MD of
this study are not same.
99
At first, single linkage method with similarity target of 0.7 was used for the
analysis due to its simplicity (Johnson & Wichern, 2002). Figure 1 demonstrates the
dendrogram obtained from this analysis. As illustrated by it, this method of cluster
analysis was not found useful in identifying major clusters in the data sets. Thus, further
cluster analysis was conducted using Ward’s method. The Ward’s method of cluster
analysis was used for its ability to minimize the ‘loss of information’ of joining groups
through weighting the clusters (Johnson & Wichern, 2002, p. 690). Using an unrestrained
analysis setting, this method generated a set of Eight (8) clusters as shown in Figure 2.
Here, all eight clusters contain logically similar questions within same group. Q 01-10
and Q 02-10 were expected to be grouped with Q 01-9 and Q 02-9 as they were designed
to reflect ‘Formal Relationship’ nature. This unexpected inclusion of Q 01-10 and Q 0210 with the group of questions regarding disruptive behavior (Q09 and Q11) indicates
that nurses consider this particular behavior stated in Q 01-10 as more similar to being
disruptive instead of formal in nature. Table 1 provides a quick overview of the clusters
and comments on similarities.
87.94
100
Q 01-1
Q 02-1
Q 05-1
Q 05-2
Q 05-3
Q 07-1
Q 07-4
Q 07-2
Q 07-3
Q 05-4
Q 01-2
Q 02-2
Q 02-3
Q 01-3
Q 01-4
Q 02-4
Q 01-5
Q 02-5
Q 03-5
Q 04-5
Q 03-1
Q 04-1
Q 03-2
Q 04-2
Q 04-3
Q 04-4
Q 03-4
Q 03-3
Q 06-1
Q 06-2
Q 06-3
Q 06-4
Q 06-5
Q 08-1
Q 08-2
Q 08-3
Q 08-4
Q 08-5
Q 10-1
Q 10-3
Q 10-2
Q 12-2
Q 12-1
Q 12-3
Q 12-5
Q 12-4
Q 10-4
Q 10-5
Q 01-6
Q 02-6
Q 03-6
Q 04-6
Q 01-7
Q 01-8
Q 02-7
Q 02-8
Q 01-10
Q 02-10
Q 01-9
Q 02-9
Q 03-9
Q 04-9
Q 09-1
Q 09-2
Q 09-3
Q 03-10
Q 04-10
Q 09-4
Q 11-1
Q 11-2
Q 11-3
Q 11-4
Q 03-7
Q 03-8
Q 04-7
Q 04-8
Similarity
Cluster Analysis of RN Data Sets (Single Linkage Method)
63.82
75.88
100.00
Variables
Figure 1: Single Linkage Dendrogram Using RN Data Sets
Q 01-1
Q 02-1
Q 01-3
Q 02-3
Q 01-4
Q 02-4
Q 01-2
Q 02-2
Q 05-1
Q 05-4
Q 05-2
Q 05-3
Q 07-1
Q 07-4
Q 07-2
Q 07-3
Q 01-5
Q 02-5
Q 03-5
Q 04-5
Q 03-1
Q 04-1
Q 03-2
Q 04-2
Q 04-3
Q 04-4
Q 03-3
Q 03-4
Q 06-1
Q 06-2
Q 06-3
Q 06-4
Q 06-5
Q 08-1
Q 08-2
Q 08-3
Q 08-4
Q 08-5
Q 10-1
Q 10-3
Q 10-4
Q 10-5
Q 10-2
Q 12-2
Q 12-1
Q 12-3
Q 12-5
Q 12-4
Q 01-6
Q 02-6
Q 03-6
Q 04-6
Q 01-9
Q 02-9
Q 03-9
Q 04-9
Q 03-10
Q 04-10
Q 03-7
Q 03-8
Q 04-7
Q 04-8
Q 01-7
Q 01-8
Q 02-7
Q 02-8
Q 01-10
Q 02-10
Q 09-1
Q 09-2
Q 09-3
Q 09-4
Q 11-1
Q 11-2
Q 11-3
Q 11-4
101
Similarity
Cluster Analysis of RN Data Sets
-419.39
-246.26
-73.13
100.00
Variables
Figure 2: Dendrogram of Cluster Analysis of RN Data Sets Using Ward’s method
102
Clusters
Cluster 1
Q 01-1 Q 01-2 Q 01-3 Q 01-4
Q 02-1 Q 02-2 Q 02-3 Q 02-4
Q 05-1 Q 05-2 Q 05-3 Q 05-4
Q 07-1 Q 07-2 Q 07-3 Q 07-4
Cluster 2
Q 01-5 Q 02-5 Q 03-5 Q 04-5
Cluster 3
Q 01-6 Q 01-9 Q 02-6 Q 02-9
Q 03-6 Q 03-9 Q 04-6 Q 04-9
Q 03-10 Q 04-10
Cluster 4
Q 01-7 Q 01-8 Q 01-10
Q 02-7 Q 02-8 Q 02-10
Q 09-1 Q 09-2 Q 09-3 Q 09-4
Q 11-1 Q 11-2 Q 11-3 Q 11-4
Cluster 5
Q 03-1 Q 03-2 Q 03-3 Q 03-4
Q 04-1 Q 04-2 Q 04-3 Q 04-4
Cluster 6
Q 03-7 Q 03-8 Q 04-7 Q 04-8
Cluster 7
Q 06-1 Q 06-2 Q 06-3 Q 06-4 Q 06-5 Q
08-1 Q 08-2 Q 08-3 Q 08-4 Q 08-5
Cluster 8
Q 10-1 Q 10-2 Q 10-3 Q 10-4 Q 10-5 Q
12-1 Q 12-2 Q 12-3 Q 12-4 Q 12-5
Comments
Descriptive norms of
positive type behavior
(both actual and
perceived)
Collegial Relationship
(All Norms)
Collaborative & Formal
type of behaviors – both
descriptive and injunctive
norms
Negative/disruptive Type
of behaviors
(Descriptive)
Injunctive norms
regarding positive
behaviors
Negative behaviors
(Injunctive)
Impact of supportive
behaviors (Actual and
Perceived)
Impact of disruptive
behaviors (Actual and
Perceived)
Cronbach’s
Alpha value
0.9120
0.8134
0.8048
0.8964
0.8683
0.6633
0.9417
0.9124
Table 1: Clusters of RN Data Sets and associated Cronbach's Alpha value
In order to further understand the internal consistency of the data sets within each
clusters, item analysis was performed using Minitab 16. Item Analysis evaluated how
reliably multiple items in a survey measures the same construct by presenting several
types of statistics. One of them is Cronbach's alpha that measures the degree of internal
consistency for all included items (Anderson 1984, Cronbach 1951). The associated
Cronbach’s Alpha value of each clusters was displayed in Table 1. All of the components
exceeded the general rule of a desired internal consistency of 0.70 or above (Cronbach,
103
2004) except for Cluster 6. The Cronbach’s alpha value for Cluster 5 was 0.6633 which is
very close to 0.7 and can be considered significant. Besides, the Item-Adj.-Total
Correlation and the Squared-Multiple Correlation value for each of the items of cluster 6
were significantly higher. This analysis gave evidence of internal consistency of the
instrument construct and supported the hypothesis 1.
Similar cluster analysis was performed with MD data sets. This analysis produced
10 clusters. Table 2 demonstrates the findings of this cluster analysis and comments on
the similarities of components of each cluster. Item analysis explored Cronbach’s Alpha
value above 0.7 for all the clusters except for cluster 9 (i.e. 0.5074). The lower
Cronbach’s alpha value for this cluster suggests a lack of consistency within the items as
a single construct. Further look into the cluster gives a possible explanation. Cluster 9
includes 4 questions – Q09-1 to Q09-4. All 4 questions asked the physicians regarding
how frequently they demonstrated mentioned disruptive behaviors. Q09-1 and Q09-2
asked about being verbally abusive to nurses and shouting at them if they make a
mistake. Q09-3 and Q09-4 asked about taking feelings of frustration, stress or anger out
on RN and not responding their concern timely. Clearly, there are strong differences
regarding the intensity of disruptiveness of Q09-1, 2 and Q09-3, 4. The responses of MD
reflects this differences as well. For example, 170 and 176 MDs (out of 186) responded
‘never’ to Q09-1 and Q09-2 respectively. In contrast, 104 and 76 MDs responded ‘never’
to Q09-3 and Q09-4 respectively. Besides, though the 4 questions were in same cluster,
there were two sub-clusters with different similarity level as demonstrated by the
dendrogram in Figure 2
104
The clusters identified for RN data sets were not completely identical to the
clusters identified by MD data sets. One of the reasons of getting this types of clusters for
RN and MD could be the difference in the norms of RN and MD. Further analysis
discussed later in this chapter supported this reason. However, regardless of their
differences, many similarities were also observed among them. Table 3 demonstrates the
similarities of different clusters of RN and MD using variety of colors. For example,
cluster 7 of RN data sets included both the actual and perceived norms of the impact of
supportive physician behaviors. For MD data sets, actual norms and perceived norms
were grouped into two clusters (cluster 7 and 8). Table 2 demonstrates the Clusters of
MD Data Sets Using Ward's Method.
105
Clusters
Comments
Cronbach’s
Alpha value
Cluster 1
MD 01-1 MD 01-3
MD 03-1 MD 03-2 MD 03-3
MD 05-1 MD 05-2 MD 05-3 MD 05-4
Actual norms of supportive
behavior (Q05), actual norms of
MD as teacher (Q01-1) and
coworker (descriptive &
injunctive)
0.7457
Cluster 2
MD 01-2
MD 01-4 MD 01-5 MD 02-4 MD 02-5
MD 03-4 MD 03-5 MD 04-4 MD 04-5
All norms regarding question
Q01-4, Q01-5
0.8103
Cluster 3
MD 01-6 MD 02-6 MD 03-6 MD 04-6
All norms regarding question
(Q01-6) “Physicians are always
in charge when deciding plan of
care”
0.7281
Cluster 4
MD 01-7 MD 01-8 MD 02-7 MD 02-8
MD 03-7 MD 03-8 MD 04-7 MD 04-8
MD 11-1 MD 11-2 MD 11-3 MD 11-4
Negative/disruptive type of
relationship nature (all norms)
and the perceived norms of
frequency of disruptive
behaviors
0.8181
All norms regarding question of
Formal type of Relationship
0.7919
Perceived norms of studentteacher, collegial relationship
nature and supportive
behaviors.
0.8429
Impact of supportive physician
behavior (Actual norms)
0.9168
Impact of supportive physician
behavior (Perceived Norms)
0.9365
Frequency of self-reported
disruptive behaviors
0.5074
Actual and perceived norms of
the impact of disruptive
behaviors
0.9478
Cluster 5
MD 01-9 MD 01-10 MD 02-9 MD 02-10
MD 03-9 MD 03-10 MD 04-9 MD 04-10
Cluster 6
MD 02-1 MD 02-2 MD 02-3
MD 04-1 MD 04-2 MD 04-3
MD 07-1 MD 07-2 MD 07-3 MD 07-4
Cluster 7
MD 06-1 MD 06-2 MD 06-3 MD 06-4
MD 06-5
Cluster 8
MD 08-1 MD 08-2 MD 08-3 MD 08-4
MD 08-5
Cluster 9
MD 09-1 MD 09-2 MD 09-3 MD 09-4
Cluster 10
MD 10-1 MD 10-2 MD 10-3 MD 10-4
MD 10-5
MD 12-1 MD 12-2 MD 12-3 MD 12-4
MD 12-5
Table 2: Clusters of MD Data Sets Using Ward's Method
106
Clusters of RN data sets
Cluster 1
Q 01-2 Q 01-3
Q 02-2 Q 02-3
Q 05-2 Q 05-3
Q 07-2 Q 07-3
Cluster 5
Q 03-1 Q 03-2 Q 03-3
Q 04-1 Q 04-2 Q 04-3
Q 01-1
Q 02-1
Q 05-1
Q 07-1
Q 01-4
Q 02-4
Q 05-4
Q 07-4
Q 03-4
Q 04-4
Cluster 2
Q 01-5 Q 02-5 Q 03-5 Q 04-5
Cluster 3
Q 01-6 Q 02-6 Q 03-6 Q 04-6
Q 01-9 Q 02-9 Q 03-9 Q 04-9
Q 03-10 Q 04-10
Cluster 4
Q 01-7 Q 01-8
Q 02-7 Q 02-8
Q 01-10 Q 02-10
Q 09-1 Q 09-2 Q 09-3 Q 09-4
Q 11-1 Q 11-2 Q 11-3 Q 11-4
Cluster 6
Q 03-7 Q 03-8
Q 04-7 Q 04-8
Cluster 7
Q 06-1 Q 06-2 Q 06-3 Q 06-4 Q 06-5
Q 08-1 Q 08-2 Q 08-3 Q 08-4 Q 08-5
Cluster 8
Q 10-1 Q 10-2 Q 10-3 Q 10-4 Q 10-5
Q 12-1 Q 12-2 Q 12-3 Q 12-4 Q 12-5
Clusters of MD data sets
Cluster 1
Q 01-1 Q 01-3
Q 03-1 Q 03-2 Q 03-3
Q 05-1 Q 05-2 Q 05-3 Q 05-4
Cluster 6
Q 02-1 Q 02-2 Q 02-3
Q 04-1 Q 04-2 Q 04-3
Q 07-1 Q 07-2 Q 07-3 Q 07-4
Cluster 2
Q 01-5 Q 02-5 Q 03-5 Q 04-5
Q 01-4 Q 02-4 Q 03-4 Q 04-4
Q 01-2
Cluster 3
Q 01-6 Q 02-6 Q 03-6 Q 04-6
Cluster 5
Q 01-9 Q 02-9 Q 03-9 Q 04-9
Q 01-10 Q 02-10 Q 03-10 Q 04-10
Cluster 4
Q 01-7 Q 01-8
Q 02-7 Q 02-8
Q 03-7 Q 03-8
Q 04-7 Q 04-8
Q 11-1 Q 11-2 Q 11-3 Q 11-4
Cluster 9
Q 09-1 Q 09-2 Q 09-3 Q 09-4
Cluster 7
Q 06-1 Q 06-2 Q 06-3 Q 06-4
Cluster 8
Q 08-1 Q 08-2 Q 08-3 Q 08-4
Cluster 10
Q 10-1 Q 10-2 Q 10-3 Q 10-4
Q 12-1 Q 12-2 Q 12-3 Q 12-4
Q 06-5
Q 08-5
Q 10-5
Q 12-5
Table 3: Quick Comparison of Clusters of RN and MD data sets
100.00
Q 01-1
Q 03-1
Q 03-2
Q 03-3
Q 01-3
Q 05-4
Q 05-1
Q 05-2
Q 05-3
Q 01-2
Q 01-4
Q 02-4
Q 04-4
Q 03-4
Q 01-5
Q 02-5
Q 03-5
Q 04-5
Q 02-1
Q 04-1
Q 02-2
Q 04-2
Q 04-3
Q 02-3
Q 07-1
Q 07-4
Q 07-2
Q 07-3
Q 06-1
Q 06-2
Q 06-3
Q 06-4
Q 06-5
Q 08-1
Q 08-2
Q 08-3
Q 08-4
Q 08-5
Q 01-6
Q 02-6
Q 03-6
Q 04-6
Q 09-1
Q 09-2
Q 09-3
Q 09-4
Q 01-7
Q 01-8
Q 03-7
Q 03-8
Q 04-7
Q 04-8
Q 02-7
Q 02-8
Q 11-1
Q 11-2
Q 11-3
Q 11-4
Q 01-9
Q 03-9
Q 04-9
Q 02-9
Q 01-10
Q 02-10
Q 03-10
Q 04-10
Q 10-1
Q 10-2
Q 10-3
Q 10-4
Q 10-5
Q 12-1
Q 12-2
Q 12-3
Q 12-4
Q 12-5
107
Similarity
Cluster Analysis of MD Data Sets using Ward's Method
-306.56
-171.04
-35.52
Variables
Figure 2: Dendrogram of Cluster Analysis of MD Data Sets Using Ward’s method
108
Factor Analysis
The cluster analysis provided support of internal consistency of the instruments.
To evaluate if there was any directional influence within the construct, further
exploratory analysis was then performed using factor analysis in Minitab. Factor analysis
is an appropriate interdependence multivariate method when the structure of variables is
to be analyzed (Anderson, Babin, Black, & Hair, 2010). Initially, unrotated principal
components method was used and Minitab 16 was allowed to extract a large number of
factors, scree plot was generated separately for RN and MD data sets. Unrotated factor
analysis was used for its ability to identify large number of significant factor loadings.
Figure 3 displays the scree plot for RN data sets. Using Kaiser Criterion, where an
acceptable factor having an Eigen value greater than 1.0 (Stevens, 2002), the analysis
indicated that first 18 factors could be recommended for use for RN data sets. These
factors explained 73.7% of the variance of data sets. As the number of variables in this
study was greater than 30, a graphical method of analysis using scree plot is
recommended (Stevens, 2002). The scree plot was used in an attempt to identify an
inflection point that could limit the factors (Johnson & Wichern, 2002). From the Scree
plot (Figure 11), factor 2 appeared as an obvious inflection. But it explained only 29.4%
of variance in cumulative which was very low and was not a good choice for cut-off
point. Factor 3 would not be a good choice as cut-off for the same reason. From the Scree
plot, factor 7 was found as the next reasonable cut-off point. The Eigen value of factor 7
was over 2.0 and it explained 52.6% of the variance of the data sets which is significantly
higher. Factor 10 could also be selected as cut-off point but it would not explain the
109
percentage of variance much higher and would not significantly load any more elements
than of factor 7. The results of this seven factors model included 71 questions that loaded
significantly (out of 76), i.e. the factor loading was greater than or equal to 0.4 when
rounded (Hair, Anderson, Tatham, & Black, 1998). This number was significantly higher
and represented the ability of the instrument to measure the RNs’ norms.
However, this ‘unrotated’ factor analysis included 19 questions that were loaded
significantly in more than one factor. This repetition causes difficulty in understanding
each factors individually. To avoid this repetition and have a more clear-cut
interpretation, rotation was used. The complete table of factor loadings from the
unrotated principal component factor analysis is displayed in Table 5.
Subsequent analysis using a variety of rotation techniques found that varimax
rotations (Johnson & Wichern, 2002) provided the cleanest factor loadings. Using Kaiser
Criterion, total 18 factors were found acceptable with Eigen value greater than 1.0
(Stevens, 2002). These 18 factors explain 47.8% of the variance of the data sets. Using
the scree plot (Stevens, 2002) as described earlier, first seven factors were selected for
further analysis. These seven factors included total of 34 different questions out of 76
questions (48.24%). This model also had 42 questions that failed to load significantly on
any of the seven factors. The complete table of factor loadings from varimax rotation is
displayed in Table 6.
The significant questions in each factors were then examined using Minitab’s
Item Analysis. The average Cronbach’s alpha value for them was found 0.8276. The
110
minimum Cronbach’s alpha for any question was 0.81807. The seven factors identified
by this analysis can be explained according to Table 4.
Factor rotation takes effort to find new axes to represent the factors. The new axes
are selected so that they go through clusters of subgroups of the points representing the
response variables. In this process, new factors are selected so that some loadings are
very large and remaining are very low (Afifi, May, & Clark, 2012). For the purpose of
this study, varimax rotation was used that further restricts the new axes to being
orthogonal to each other. Thus, it is not surprising that many variables (that were
significantly loaded in unrotated factor analysis) fails to be loaded significantly in rotated
factor analysis.
Cronbach’s
alpha
Factor #
Components
Factor 1
Q 06-2 to Q 06-5
Q 08-1 to Q 08-5
0.9419
Factor 2
Q 10-1 to Q 10-5
Q 12-1 to Q 12-3
Q 12-5
0.9094
Factor 3
Q 11-1 to Q 11-4
0.8775
Factor 4
Q 07-1 to Q 07-4
0.8806
Factor 5
Q 03-1 & Q 04-1
0.8114
Factor 6
Q 03-5 & Q 04-5
0.8486
Factor 7
Q 1-10 & Q 2-10
0.8558
Comments
Impact of supportive physician
behaviors (Actual & Perceived
Norms)
Impact of disruptive physician
behaviors (Actual & Perceived
Norms)
Number of physicians display
disruptive behaviors (Perceived)
Number of physicians display
supportive behaviors (Perceived)
Physician as teacher (Injunctive
norms)
Collegial Relationship (Injunctive
norms)
Formal Relationship type
(Descriptive)
Table 4: Summary of the results of Factor analysis (RN Data Sets)
111
Scree Plot of Q 01-1, ..., Q 12-5
14
12
Eigenvalue
10
8
6
4
2
0
1
5
10
15
20
25
30 35 40 45
Factor Number
50
55
60
65
70
75
Figure 3: Scree Plot of Factor Analysis of RN Data Sets (Unrotated)
Similar factor analysis was performed with MD data sets. The unrotated FA was
able to explain 76.4% of the variances and significantly loaded 68 questions out of 76 in
first 7 factors. However, this analysis loaded 21 questions in more than one factor and
thus a varimax rotation was used to avoid rotation and get better understanding of the
factors. Figure 3, Table 5 and table 6 demonstrates the details of these findings. Using
Kaiser Criterion, 20 factors could be recommended whose Eigen values were found
greater than 1.0. Using the Scree plot, first 9 factors were selected for further analysis.
They explained 32.8% of the variance of data sets. These nine factors included total 30
different questions out of 76 questions (39.47%). This model also had 46 questions that
failed to load significantly on any of the nine factors. The components of each factors
were explained in Appendix E. Similar type of questions were found within same factor
in both factor analysis of RN and MD data sets.
112
Table 5: Unrotated Factor Loadings of FA of the Covariance Matrix (RN)
Variable
Q 01-1
Q 01-2
Q 01-3
Q 01-4
Q 01-5
Q 01-6
Q 01-7
Q 01-8
Q 01-9
Q 01-10
Q 02-1
Q 02-2
Q 02-3
Q 02-4
Q 02-5
Q 02-6
Q 02-7
Q 02-8
Q 02-9
Q 02-10
Q 03-1
Q 03-2
Q 03-3
Q 03-4
Q 03-5
Q 03-6
Q 03-7
Q 03-8
Q 03-9
Q 03-10
Q 04-1
Q 04-2
Q 04-3
Q 04-4
Q 04-5
Q 04-6
Q 04-7
Q 04-8
Q 04-9
Q 04-10
Q 05-1
Q 05-2
Q 05-3
Q 05-4
Q 06-1
Q 06-2
Q 06-3
Q 06-4
Q 06-5
Q 07-1
Q 07-2
Q 07-3
Q 07-4
Q 08-1
Q 08-2
Q 08-3
Q 08-4
Factor1
0.702
0.480
0.543
0.529
0.435
-0.285
-0.634
-0.643
-0.423
-0.644
0.728
0.533
0.564
0.596
0.476
-0.359
-0.607
-0.638
-0.420
-0.658
0.282
0.297
0.211
0.194
0.190
-0.015
-0.229
-0.232
-0.139
-0.125
0.263
0.229
0.241
0.204
0.187
0.002
-0.155
-0.172
-0.151
-0.118
0.579
0.536
0.694
0.643
0.418
0.498
0.568
0.549
0.593
0.516
0.528
0.615
0.586
0.353
0.450
0.487
0.440
Factor2
0.099
0.004
0.028
-0.033
-0.048
-0.045
-0.215
-0.159
-0.142
-0.099
0.127
-0.005
0.118
0.014
0.003
-0.031
-0.199
-0.222
-0.113
-0.125
-0.271
-0.380
-0.220
-0.348
-0.349
-0.031
0.228
0.178
-0.053
0.107
-0.289
-0.453
-0.417
-0.408
-0.314
0.050
0.133
0.122
-0.021
0.106
0.233
0.067
0.240
0.201
-0.453
-0.421
-0.383
-0.386
-0.406
0.244
0.215
0.231
0.162
-0.562
-0.453
-0.419
-0.452
Factor3
0.122
0.191
0.195
0.144
0.121
-0.127
-0.076
-0.073
-0.142
-0.247
0.074
0.103
0.058
0.161
0.153
-0.197
0.034
-0.103
-0.092
-0.144
0.412
0.395
0.441
0.439
0.287
-0.213
-0.293
-0.257
-0.322
-0.391
0.454
0.408
0.392
0.425
0.249
-0.216
-0.026
-0.063
-0.284
-0.341
0.101
0.071
0.123
-0.003
-0.258
-0.395
-0.404
-0.424
-0.397
-0.073
0.002
-0.043
-0.105
-0.300
-0.494
-0.525
-0.539
Factor4
-0.019
0.024
-0.146
-0.071
-0.302
-0.349
-0.175
-0.220
-0.490
-0.262
-0.083
-0.005
-0.085
-0.098
-0.324
-0.327
-0.201
-0.202
-0.470
-0.269
-0.342
-0.170
-0.161
-0.235
-0.460
-0.487
0.203
0.048
-0.459
-0.237
-0.327
-0.177
-0.283
-0.302
-0.423
-0.417
0.162
0.039
-0.440
-0.154
0.076
0.059
0.039
-0.071
-0.002
-0.030
-0.043
-0.060
-0.038
-0.196
-0.062
-0.053
-0.177
-0.061
-0.103
-0.103
-0.126
Factor5
-0.161
-0.131
-0.196
-0.241
-0.339
-0.252
0.099
0.103
-0.202
0.033
-0.229
-0.088
-0.276
-0.326
-0.359
-0.218
0.127
0.096
-0.199
-0.009
0.150
0.278
0.212
0.181
-0.097
-0.289
-0.085
-0.086
-0.294
-0.370
0.162
0.250
0.149
0.130
-0.021
-0.283
0.002
-0.207
-0.273
-0.318
-0.088
-0.210
-0.018
-0.078
0.077
0.134
0.241
0.259
0.209
-0.062
-0.135
-0.040
-0.047
0.165
0.198
0.278
0.316
Factor6
-0.116
-0.088
-0.225
-0.279
-0.140
-0.128
0.153
0.150
0.204
0.176
0.026
0.042
-0.029
-0.160
-0.179
-0.230
-0.165
-0.090
0.092
0.072
-0.067
0.292
0.310
0.135
-0.001
-0.141
0.218
0.100
0.167
0.104
0.045
0.314
0.279
0.247
-0.082
-0.104
0.209
0.266
0.175
0.110
-0.062
-0.051
-0.131
-0.157
-0.137
-0.076
-0.101
-0.120
-0.030
0.178
0.121
0.154
0.263
-0.076
0.003
-0.016
-0.054
Factor7
-0.262
-0.114
0.018
-0.083
0.024
0.126
0.100
0.211
-0.128
0.035
0.008
0.138
0.228
-0.074
0.181
-0.062
-0.128
-0.081
-0.215
-0.169
0.021
-0.126
-0.210
-0.317
0.105
0.099
-0.185
-0.139
-0.255
-0.196
0.047
-0.178
-0.106
-0.145
0.094
0.132
-0.471
-0.317
-0.299
-0.308
-0.342
-0.368
-0.127
-0.122
-0.165
-0.114
-0.120
-0.120
-0.088
0.240
0.194
0.243
0.278
0.089
0.091
0.077
0.065
113
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
08-5
09-1
09-2
09-3
09-4
10-1
10-2
10-3
10-4
10-5
11-1
11-2
11-3
11-4
12-1
12-2
12-3
12-4
12-5
0.490
-0.392
-0.518
-0.116
0.259
-0.026
-0.398
-0.220
0.174
-0.208
-0.078
-0.079
-0.439
-0.175
0.189
-0.238
-0.027
-0.046
-0.392
-0.261
0.061
-0.344
-0.018
-0.204
-0.521
-0.248
0.202
-0.087
0.144
0.042
0.071
-0.678
0.021
0.306
-0.222
0.138
0.062
-0.606
0.065
0.342
-0.342
0.165
-0.085
-0.681
0.014
0.293
-0.275
0.100
-0.133
-0.478
-0.088
0.283
-0.296
0.209
-0.137
-0.530
0.024
0.307
-0.353
0.219
-0.441
-0.293
0.178
0.093
-0.013
-0.491
-0.374
-0.310
0.163
0.020
0.004
-0.537
-0.391
-0.378
0.182
-0.033
0.087
-0.507
-0.475
-0.343
0.094
0.169
0.059
-0.351
0.098
-0.726
0.015
0.306
-0.235
0.031
0.041
-0.666
-0.010
0.305
-0.341
0.053
-0.041
-0.711
0.063
0.209
-0.239
-0.066
-0.087
-0.564
-0.027
0.171
-0.225
0.022
-0.048
-0.666
0.080
0.228
-0.313
0.076
# of significant Loadings in Factors (>0.4)
45
25
17
8
2
4
2
Variance
% Var
13.728
0.181
8.578
0.113
4.826
0.064
4.330
0.057
3.257
0.043
0.107
0.283
0.302
0.305
0.097
0.171
0.176
0.238
0.092
0.181
-0.151
-0.112
-0.156
-0.235
-0.049
-0.016
-0.121
-0.135
-0.099
2.572
0.034
2.548
0.034
Scree Plot of Q 01-1, ..., Q 12-5
14
12
Eigenvalue
10
8
6
4
2
0
1
5
10
15
20
25
30 35 40 45
Factor Number
50
55
60
65
70
75
Figure 4: Scree Plot of FA of RN Data Sets Using Varimax Rotation
114
Table 6: Varimax rotated Factor Loadings (RN)
Variable
Q 01-1
Q 01-2
Q 01-3
Q 01-4
Q 01-5
Q 01-6
Q 01-7
Q 01-8
Q 01-9
Q 01-10
Q 02-1
Q 02-2
Q 02-3
Q 02-4
Q 02-5
Q 02-6
Q 02-7
Q 02-8
Q 02-9
Q 02-10
Q 03-1
Q 03-2
Q 03-3
Q 03-4
Q 03-5
Q 03-6
Q 03-7
Q 03-8
Q 03-9
Q 03-10
Q 04-1
Q 04-2
Q 04-3
Q 04-4
Q 04-5
Q 04-6
Q 04-7
Q 04-8
Q 04-9
Q 04-10
Q 05-1
Q 05-2
Q 05-3
Q 05-4
Q 06-1
Q 06-2
Q 06-3
Q 06-4
Q 06-5
Q 07-1
Q 07-2
Q 07-3
Q 07-4
Q 08-1
Q 08-2
Q 08-3
Q 08-4
Factor1
0.108
0.039
0.082
0.123
0.081
-0.090
-0.082
-0.084
-0.038
-0.057
0.139
0.102
0.079
0.084
0.067
-0.032
-0.090
-0.022
-0.037
-0.113
0.024
0.104
0.013
0.049
0.082
0.045
-0.064
-0.029
0.068
-0.009
0.062
0.109
0.103
0.071
0.099
0.046
-0.089
-0.102
0.023
-0.026
-0.005
0.050
0.052
0.125
0.331
0.517
0.556
0.583
0.573
0.122
0.092
0.198
0.252
0.643
0.822
0.955
0.951
Factor2
0.028
-0.057
0.002
-0.015
0.005
0.000
-0.056
0.007
0.001
0.042
0.012
-0.035
-0.010
-0.029
-0.001
0.033
0.021
0.014
0.030
0.024
-0.038
-0.092
-0.031
-0.060
-0.101
0.037
0.070
0.079
0.010
0.026
-0.062
-0.144
-0.115
-0.087
-0.050
0.047
0.055
-0.035
0.033
0.001
0.076
-0.028
0.119
0.127
-0.186
-0.124
-0.071
-0.052
-0.124
0.149
0.071
0.091
0.082
-0.221
-0.125
-0.078
-0.063
Factor3
-0.085
-0.050
-0.039
-0.034
-0.034
0.031
0.081
0.070
0.023
0.052
-0.157
-0.135
-0.116
-0.065
-0.057
0.064
0.243
0.185
0.084
0.140
0.013
-0.030
-0.037
0.060
0.019
-0.007
-0.040
-0.002
-0.025
-0.052
0.043
0.005
-0.014
0.026
0.027
-0.048
0.028
-0.016
-0.009
-0.036
-0.089
-0.048
-0.113
-0.073
-0.003
-0.036
-0.076
-0.049
-0.099
-0.192
-0.119
-0.159
-0.195
0.081
-0.052
-0.026
-0.017
Factor4
-0.114
-0.090
-0.119
-0.043
-0.126
0.068
0.078
0.087
0.112
0.122
-0.263
-0.103
-0.169
-0.161
-0.126
0.126
0.115
0.146
0.097
0.137
0.010
-0.015
-0.035
-0.002
-0.022
0.011
-0.001
0.037
0.052
-0.010
-0.048
0.034
-0.019
-0.022
0.009
-0.047
0.019
0.031
0.017
-0.044
-0.109
-0.225
-0.350
-0.103
0.030
-0.026
-0.015
0.008
-0.040
-0.350
-0.910
-0.715
-0.446
-0.032
-0.073
-0.081
0.001
Factor5
-0.090
-0.017
-0.064
-0.046
-0.023
-0.043
0.026
0.066
-0.017
0.038
-0.098
-0.095
-0.082
-0.055
-0.038
0.010
0.031
0.099
0.012
0.021
-0.839
-0.186
-0.170
-0.174
-0.207
-0.013
0.359
0.144
0.001
0.065
-0.874
-0.268
-0.219
-0.183
-0.112
-0.002
0.106
0.078
-0.002
0.060
-0.019
-0.034
-0.100
-0.043
-0.041
-0.035
-0.033
-0.043
-0.072
-0.033
-0.014
-0.024
0.013
-0.093
0.011
0.000
-0.014
Factor6
0.031
-0.028
0.074
0.055
0.262
0.030
-0.002
0.011
0.062
-0.060
0.075
-0.002
-0.013
0.061
0.311
0.002
0.029
0.040
0.041
0.013
0.158
0.070
0.129
0.132
0.820
0.091
-0.070
-0.018
0.027
-0.016
0.147
0.121
0.183
0.209
0.902
0.046
-0.083
-0.064
-0.008
-0.065
-0.026
0.031
0.012
0.028
0.069
0.044
0.014
0.027
0.034
0.020
0.027
-0.040
0.026
0.038
0.071
0.019
0.028
Factor7
0.106
0.071
0.122
0.168
0.089
-0.097
-0.206
-0.181
-0.210
-0.757
0.160
0.099
0.154
0.158
0.127
-0.089
-0.176
-0.240
-0.144
-0.801
0.039
0.038
0.027
0.022
0.005
-0.083
-0.032
-0.039
-0.105
-0.085
0.008
0.029
0.028
0.007
0.015
-0.031
-0.035
-0.047
-0.123
-0.088
0.133
0.112
0.159
0.210
0.050
0.041
0.022
0.043
0.062
0.092
0.103
0.092
0.088
0.020
0.015
0.017
0.026
115
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
08-5
09-1
09-2
09-3
09-4
10-1
10-2
10-3
10-4
10-5
11-1
11-2
11-3
11-4
12-1
12-2
12-3
12-4
12-5
0.939
-0.061
-0.036
-0.090
-0.030
0.047
-0.125
-0.098
0.156
0.006
-0.029
0.043
-0.140
-0.028
0.160
0.052
0.005
0.068
-0.016
0.000
0.223
0.044
-0.042
0.071
-0.173
-0.084
0.076
0.127
-0.006
-0.006
0.152
-0.688
-0.007
0.036
-0.028
0.051
0.073
-0.889
0.008
0.021
-0.035
0.055
0.093
-0.597
0.065
0.045
0.044
-0.020
0.049
-0.352
0.056
0.032
0.073
-0.004
0.006
-0.546
0.067
0.019
-0.020
0.020
-0.094
-0.116
0.780
0.051
0.004
-0.012
-0.042
-0.083
0.939
0.105
-0.027
0.008
-0.023
-0.082
0.773
0.123
-0.045
0.066
-0.095
-0.183
0.452
0.134
0.011
-0.044
0.166
-0.791
0.069
0.050
-0.059
0.023
0.140
-0.924
0.099
0.037
-0.032
0.035
0.088
-0.562
0.112
0.094
-0.008
0.033
0.105
-0.324
0.121
0.039
0.028
0.015
0.063
-0.616
0.133
0.034
-0.021
0.044
# of significant Loadings in Factors (>0.4)
9
9
4
5
3
2
2
Variance
% Var
5.7153
0.075
4.7372
0.062
2.8786
0.038
2.3127
0.030
2.0675
0.027
1.9466
0.026
0.046
-0.099
-0.151
-0.107
-0.096
0.025
0.026
-0.042
-0.062
-0.034
-0.054
-0.055
-0.055
-0.070
0.056
0.001
0.005
-0.046
-0.037
1.9187
0.025
Scree Plot of Q 01-1, ..., Q 12-5
12
10
Eigenvalue
8
6
4
2
0
1
5
10
15
20
25
30 35 40 45
Factor Number
50
55
60
65
70
75
Figure 5: Scree Plot of FA of MD Data Sets Using Varimax Rotation
116
Table 7: Unrotated Factor Loadings of Principal Component Factor Analysis of the
Covariance Matrix (MD Data Sets)
Variable
Q 01-1
Q 01-2
Q 01-3
Q 01-4
Q 01-5
Q 01-6
Q 01-7
Q 01-8
Q 01-9
Q 01-10
Q 02-1
Q 02-2
Q 02-3
Q 02-4
Q 02-5
Q 02-6
Q 02-7
Q 02-8
Q 02-9
Q 02-10
Q 03-1
Q 03-2
Q 03-3
Q 03-4
Q 03-5
Q 03-6
Q 03-7
Q 03-8
Q 03-9
Q 03-10
Q 04-1
Q 04-2
Q 04-3
Q 04-4
Q 04-5
Q 04-6
Q 04-7
Q 04-8
Q 04-9
Q 04-10
Q 05-1
Q 05-2
Q 05-3
Q 05-4
Q 06-1
Q 06-2
Q 06-3
Q 06-4
Q 06-5
Q 07-1
Q 07-2
Q 07-3
Q 07-4
Q 08-1
Q 08-2
Q 08-3
Factor1
0.339
0.180
0.296
0.349
0.271
0.098
-0.181
-0.241
-0.033
-0.230
0.487
0.358
0.412
0.382
0.487
0.164
-0.443
-0.416
-0.212
-0.499
0.302
0.307
0.314
0.279
0.427
0.115
-0.266
-0.200
-0.048
-0.115
0.506
0.513
0.509
0.495
0.477
0.151
-0.465
-0.450
-0.279
-0.267
0.301
0.393
0.451
0.514
0.431
0.538
0.591
0.583
0.574
0.354
0.542
0.449
0.456
0.510
0.611
0.667
Factor2
-0.100
-0.199
-0.211
-0.077
-0.080
-0.182
0.149
0.122
0.191
0.272
-0.310
-0.337
-0.199
-0.184
-0.120
0.011
0.150
0.179
0.244
0.416
-0.261
-0.242
-0.276
-0.082
-0.045
-0.120
0.276
0.267
0.091
0.247
-0.141
-0.352
-0.328
-0.129
-0.051
-0.019
0.389
0.287
0.155
0.321
-0.078
0.029
-0.004
-0.152
0.224
0.274
0.243
0.225
0.279
-0.164
-0.190
-0.363
-0.205
0.125
0.142
0.130
Factor3
0.230
0.272
0.211
0.342
0.246
-0.175
-0.031
-0.139
-0.280
-0.214
-0.213
0.080
-0.330
-0.005
-0.076
-0.364
0.212
0.417
-0.136
0.036
0.320
0.472
0.379
0.561
0.457
-0.217
0.096
0.033
-0.296
-0.304
-0.156
0.069
-0.106
0.107
0.125
-0.370
0.080
0.250
-0.062
-0.068
0.397
0.260
0.283
0.257
0.181
0.195
0.306
0.344
0.365
-0.171
-0.201
-0.229
-0.230
-0.332
-0.342
-0.299
Factor4
-0.077
0.216
0.148
0.179
0.374
0.077
0.394
0.365
0.508
0.400
-0.005
0.256
0.137
0.389
0.377
-0.028
0.138
0.039
0.285
0.168
-0.093
0.065
-0.085
0.185
0.159
0.139
0.568
0.639
0.514
0.376
-0.093
0.039
-0.027
0.236
0.308
0.006
0.337
0.423
0.456
0.423
0.123
0.111
0.056
0.044
0.167
0.063
-0.080
-0.060
0.029
0.327
0.241
0.313
0.387
0.213
0.032
0.015
Factor5
0.012
0.344
-0.150
0.303
-0.116
-0.321
0.220
0.429
-0.183
-0.010
0.229
0.381
-0.001
0.212
0.032
-0.222
-0.105
0.014
-0.328
-0.216
-0.017
0.185
0.125
0.244
0.137
-0.167
0.150
0.159
-0.204
-0.219
-0.010
0.302
0.242
0.255
0.189
-0.263
0.037
0.131
-0.292
-0.137
-0.440
-0.322
-0.397
-0.276
-0.466
-0.380
-0.285
-0.187
-0.167
0.019
0.145
0.168
0.026
-0.118
-0.098
0.035
Factor6
0.175
0.112
0.106
-0.024
0.014
0.160
0.009
0.058
0.174
0.048
0.106
-0.010
-0.045
0.026
-0.119
0.350
0.091
0.161
0.134
0.029
0.454
0.201
0.219
0.203
0.060
0.389
-0.047
-0.122
0.222
0.022
0.227
0.052
-0.033
-0.041
-0.122
0.224
-0.121
-0.081
0.171
0.074
0.130
0.105
-0.069
0.111
-0.238
-0.236
-0.278
-0.247
-0.287
0.321
0.228
0.090
0.219
-0.291
-0.329
-0.380
Factor7
0.174
-0.272
0.223
-0.326
-0.216
0.334
0.270
0.151
-0.196
0.213
0.058
0.011
0.081
-0.138
-0.139
0.343
-0.224
-0.020
-0.416
0.033
0.227
0.229
0.179
-0.110
-0.101
0.238
0.152
0.086
-0.102
0.350
0.340
0.170
0.174
-0.068
-0.019
0.335
-0.148
0.096
-0.250
0.190
-0.046
0.058
-0.068
-0.067
0.117
0.115
0.035
0.026
0.040
-0.019
-0.162
-0.084
-0.002
0.058
0.020
0.014
117
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
08-4
08-5
09-1
09-2
09-3
09-4
10-1
10-2
10-3
10-4
10-5
11-1
11-2
11-3
11-4
12-1
12-2
12-3
12-4
12-5
Variance
% Var
-0.401
-0.400
-0.220
-0.190
-0.112
-0.193
0.159
0.149
0.183
0.211
0.254
-0.307
-0.205
-0.058
-0.049
0.050
0.027
0.251
0.243
0.211
0.038
0.038
-0.203
-0.129
0.164
0.333
-0.013
-0.040
-0.044
-0.079
-0.102
0.219
0.300
0.386
0.375
0.046
0.044
-0.079
-0.081
-0.066
Number of variables loaded significantly
36
13
10
15
7
6
11.193
7.884
4.748
4.455
3.592
2.938
0.147
0.104
0.062
0.059
0.047
0.039
3
2.540
0.033
0.661
0.663
-0.087
-0.065
-0.193
-0.179
0.364
0.336
0.314
0.312
0.324
-0.323
-0.291
-0.236
-0.213
0.389
0.279
0.301
0.364
0.342
0.152
0.105
-0.026
-0.000
0.089
0.015
0.662
0.713
0.695
0.752
0.734
0.168
0.302
0.292
0.318
0.635
0.740
0.684
0.677
0.740
-0.279
-0.283
-0.325
-0.210
-0.154
-0.173
0.022
0.039
-0.154
-0.126
-0.094
0.371
0.326
0.345
0.322
0.060
0.078
-0.068
-0.047
-0.048
0.073
0.087
0.034
-0.008
-0.049
-0.154
-0.047
-0.136
-0.191
-0.155
-0.119
0.239
0.266
0.074
0.055
-0.053
-0.122
-0.192
-0.185
-0.118
0.123
-0.009
0.223
0.206
0.389
0.304
0.084
0.102
0.209
0.223
0.138
0.095
0.162
0.084
0.250
-0.009
0.033
0.199
0.165
0.125
118
Table 8: Varimax rotated Factor Loadings of Principal Component Factor Analysis of the
Covariance Matrix (MD Data sets)
Variable
Q 01-1
Q 01-2
Q 01-3
Q 01-4
Q 01-5
Q 01-6
Q 01-7
Q 01-8
Q 01-9
Q 01-10
Q 02-1
Q 02-2
Q 02-3
Q 02-4
Q 02-5
Q 02-6
Q 02-7
Q 02-8
Q 02-9
Q 02-10
Q 03-1
Q 03-2
Q 03-3
Q 03-4
Q 03-5
Q 03-6
Q 03-7
Q 03-8
Q 03-9
Q 03-10
Q 04-1
Q 04-2
Q 04-3
Q 04-4
Q 04-5
Q 04-6
Q 04-7
Q 04-8
Q 04-9
Q 04-10
Q 05-1
Q 05-2
Q 05-3
Q 05-4
Q 06-1
Q 06-2
Q 06-3
Q 06-4
Q 06-5
Q 07-1
Q 07-2
Q 07-3
Q 07-4
Q 08-1
Q 08-2
Q 08-3
Q 08-4
Q 08-5
Q 09-1
Q 09-2
Q 09-3
Q 09-4
Q 10-1
Factor1
0.037
-0.050
-0.081
0.011
-0.003
-0.159
0.004
0.016
0.075
0.110
-0.017
-0.056
-0.023
-0.055
-0.011
0.060
-0.043
-0.024
0.013
0.102
-0.030
0.003
0.015
0.055
0.065
-0.020
0.021
0.007
0.043
0.049
0.056
-0.034
-0.028
-0.002
0.015
-0.021
0.038
0.021
-0.057
0.127
-0.013
0.057
-0.019
-0.054
0.120
0.138
0.150
0.133
0.173
0.007
0.084
-0.087
-0.028
0.121
0.113
0.135
0.145
0.113
0.010
-0.018
0.079
-0.005
0.798
Factor2
0.059
-0.030
0.021
0.122
0.005
-0.045
-0.017
-0.027
0.035
-0.025
0.213
0.122
0.216
0.161
0.194
0.031
-0.170
-0.251
-0.029
-0.149
-0.071
0.012
0.028
-0.088
-0.001
-0.010
-0.069
0.020
0.063
0.029
0.172
0.134
0.253
0.148
0.125
0.096
-0.148
-0.157
-0.128
-0.050
0.018
0.050
0.141
0.111
0.043
0.159
0.212
0.191
0.275
0.084
0.157
0.212
0.133
0.459
0.646
0.902
0.903
0.865
0.041
0.080
-0.055
0.068
0.115
Factor3
-0.133
0.013
-0.099
-0.071
-0.140
-0.084
0.053
0.115
0.005
0.114
0.068
-0.032
-0.002
0.033
-0.106
-0.022
0.075
0.022
0.062
0.069
-0.065
-0.145
-0.078
-0.124
-0.220
0.062
-0.005
0.012
0.057
0.066
-0.058
-0.084
-0.036
-0.112
-0.180
-0.011
0.016
-0.023
0.037
0.093
-0.142
-0.146
-0.321
-0.249
-0.587
-0.572
-0.883
-0.895
-0.765
0.034
-0.050
0.058
-0.084
-0.045
-0.069
-0.185
-0.208
-0.207
0.053
0.017
0.086
0.115
-0.119
Factor4
0.036
0.016
-0.046
0.072
-0.053
-0.006
0.005
0.010
0.030
-0.023
0.007
-0.089
-0.001
0.043
0.013
0.075
-0.029
0.039
0.091
-0.003
-0.007
-0.115
-0.099
0.011
0.057
0.006
0.009
0.015
-0.083
0.026
0.069
-0.058
-0.067
0.050
0.067
0.058
0.086
-0.050
-0.009
-0.003
-0.038
0.056
0.045
0.064
-0.021
0.119
0.092
0.135
0.109
0.026
0.047
-0.063
-0.010
0.057
0.137
0.103
0.109
0.050
-0.058
-0.009
-0.001
-0.049
0.176
Factor5
0.036
0.007
0.032
-0.024
-0.040
-0.015
-0.043
-0.126
-0.708
-0.141
0.039
-0.053
0.022
-0.025
-0.076
-0.060
-0.079
-0.039
-0.359
-0.083
-0.026
0.089
0.010
0.032
0.041
-0.053
-0.055
-0.115
-0.939
-0.188
-0.028
0.098
0.045
0.037
0.003
-0.105
-0.129
-0.054
-0.657
-0.098
-0.033
-0.000
0.055
0.111
-0.114
-0.011
0.043
0.086
-0.009
-0.089
-0.063
-0.009
-0.129
-0.085
-0.076
-0.008
0.007
-0.004
-0.027
0.001
0.030
0.081
-0.036
Factor6
-0.021
-0.050
-0.004
0.059
0.019
-0.057
0.059
0.092
-0.033
0.073
-0.095
-0.027
-0.057
0.039
-0.003
-0.143
-0.000
0.110
0.013
0.152
-0.032
0.020
-0.052
0.021
-0.004
-0.077
0.148
0.162
-0.005
0.005
-0.076
-0.056
-0.142
-0.059
0.052
-0.112
0.121
0.167
0.040
0.104
-0.002
0.018
-0.034
-0.058
0.057
0.008
-0.032
-0.036
0.015
-0.079
-0.162
-0.064
-0.112
0.044
-0.010
-0.079
-0.039
-0.056
-0.061
-0.024
0.020
0.009
-0.037
Factor7 Factor8
-0.035 -0.025
-0.093 -0.090
-0.090
0.006
-0.078 -0.047
-0.064 -0.237
-0.062 -0.011
-0.036 -0.059
-0.021 -0.040
-0.093
0.092
0.016 -0.014
-0.206 -0.073
-0.163 -0.101
-0.124 -0.070
-0.169 -0.050
-0.085 -0.346
-0.019
0.020
0.116
0.029
0.148 -0.012
0.024
0.074
0.143
0.055
-0.050 -0.013
-0.080 -0.062
0.010 -0.006
-0.048 -0.152
-0.066 -0.581
-0.001 -0.003
-0.013
0.016
0.002 -0.039
-0.023 -0.023
0.034
0.003
-0.108 -0.088
-0.152 -0.202
-0.066 -0.133
-0.077 -0.276
-0.056 -0.888
0.039
0.019
0.036
0.129
0.045
0.013
0.046 -0.028
0.034
0.006
-0.013 -0.009
-0.071 -0.033
-0.157
0.016
-0.069 -0.079
0.026 -0.088
0.001 -0.066
0.011 -0.109
-0.030 -0.045
0.064 -0.113
-0.318 -0.065
-0.705
0.019
-0.866 -0.092
-0.383 -0.068
-0.093 -0.059
-0.062 -0.021
-0.080 -0.042
-0.086 -0.040
-0.112 -0.055
-0.008
0.002
0.006 -0.018
0.053
0.013
-0.002
0.019
0.075 -0.012
Factor9
0.024
-0.040
-0.001
0.017
-0.030
-0.056
0.022
0.099
-0.037
0.037
0.001
-0.058
-0.015
-0.002
0.000
0.008
0.036
0.021
0.021
-0.022
-0.044
-0.003
0.016
-0.044
0.033
0.010
-0.045
0.010
0.010
-0.016
-0.050
-0.077
0.040
0.002
0.013
0.024
0.029
0.049
0.021
-0.053
-0.060
-0.075
-0.055
-0.057
-0.049
-0.004
-0.027
0.055
-0.075
0.027
0.022
-0.015
-0.046
-0.019
0.025
-0.003
0.111
-0.009
0.443
0.949
0.116
0.004
-0.100
119
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
10-2
10-3
10-4
10-5
11-1
11-2
11-3
11-4
12-1
12-2
12-3
12-4
12-5
0.818
0.890
0.893
0.864
-0.096
0.017
-0.019
0.088
0.293
0.383
0.386
0.373
0.455
9
Variance
% Var
5
4.7162
0.062
0.066
-0.126
0.240
-0.003
-0.009
0.042
0.110
-0.056
0.254
0.029
-0.024
-0.028
0.099
-0.087
0.313
-0.007
-0.019
-0.037
0.096
-0.126
0.289
-0.084
-0.029
0.021
-0.077
0.025
-0.020
0.007
0.917
0.092
-0.098
0.023
0.063
-0.004
0.778
0.060
-0.096
-0.049
0.132
0.026
0.354
0.153
-0.059
0.002
0.110
-0.001
0.293
0.067
0.108
-0.180
0.651
0.000
0.062
0.003
0.063
-0.159
0.647
0.055
0.073
0.039
0.062
-0.029
0.868
0.054
-0.042
0.015
0.106
-0.078
0.879
0.029
-0.004
0.004
0.124
-0.127
0.789
-0.019
0.041
0.003
# of significant Loadings in Factors (>0.4)
5
5
4
3
3
2
0.017
0.012
-0.035
-0.016
-0.023
-0.048
0.110
0.053
-0.081
-0.019
-0.027
-0.038
0.016
4.0163
0.053
1.6542
0.022
3.6447
0.048
3.5897
0.047
2.2413
0.029
2.0108
0.026
1.9231
0.025
-0.037
0.036
0.051
-0.008
-0.042
0.015
-0.008
-0.054
-0.092
-0.062
-0.013
0.034
0.021
2
1.2395
0.016
Table 9: Summary of the results of Factor analysis (MD Data Sets)
Factor #
Components
Cronbach’s
alpha
Comments
Factor 1
Q 10-1 to Q 10-5
0.9478
Impact of disruptive physician
behaviors (Actual Norms)
Factor 2
Q 08-1 to Q 08-5
0.9365
Impact of Supportive Behavior
(Perceived Norms)
Factor 3
Q 06-1 to Q 06-5
0.9168
Factor 4
Q 12-1 to Q 12-5
0.9341
Factor 5
Q 01-9 Q 02-9
Q 03-9 Q 04-9
0.8189
Factor 6
Q 11-1 to Q 11-3
0.8404
Factor 7
Q 07-2 to Q 07-4
0.8378
Q 03-5 & Q 04-5
0.7780
Q 09-1 & Q 09-2
0.7444
Factor 8
Factor 9
Impact of Supportive Behavior (Actual
norms)
Impact of Disruptive Behaviors
(Perceived Norms)
Formal Relationship nature (All
norms)
Perceived Frequency of disruptive
behaviors
Perceived frequency of supportive
behavior
Collegial relationship (Injunctive
norms)
Impact of disruptive behavior (Actual)
120
Conclusion of Factor analysis and Cluster Analysis
Regardless of the facts that the findings of cluster analysis and factor analysis
were not completely identical for any of the data sets, there were great number of
similarities among both RN and MD data sets. The unrotated factor analysis was able to
significantly load 71 and 68 questions of the RN and MD data sets respectively. Though
many questions were failed to be loaded significantly in the varimax rotation, the
questions that were identified as significant in this analysis were very much similar to the
findings of cluster analysis. For example, Cluster 7 and 8 of RN data sets were
completely identical to the factor 1 and 2 respectively. The components of other factors
were the subsets of their respective clusters. Similar relevance were found for MD data
sets as well. For example, factor 2 and factor 3 were completely identical with cluster 8
and cluster 7 respectively. Cluster 10 included all the components of factor 1 and factor
4. The remaining factors were the subsets of different clusters of MD data sets. These
similarities provided evidences to reject hypothesis 1, i.e. the data collection instrument
was able to measure the relationship norms of RN and MD in a valid way (reject H0)
In addition, findings of both analysis were logical, reasonable and in most cases,
reflects the constructed groups of the data collection instruments within same clusters or
factors. The Cronbach’s alpha value for almost all the clusters and factors were found
significantly high. This gave another evidence of the internal consistency of the data
collection instruments in order to measure respective relationship norms.
121
APPENDIX F
DATA ANALYSIS USING 2-SAMPLE T-TEST AND 2-PROPORTIONS TEST
APPENDIX F1: RESULTS OF ACTUAL VS PERCEIVED NORMS OF RELATIONSHIP
NATURE (DESCRIPTIVE)
Table 26: Results on 'Physician as Teacher' (Q01-1: Physicians are willing to explain issues regarding patient care to nurses)
% Response
RN Actual
(RN Q01-1)
Never
Seldom
About Half
the time
Usually
Always
1%
6%
RN
Perceived
(RN Q02-1)
0%
8%
17%
56%
20%
MD Actual
(MD Q01-1)
MD Perceived
(MD Q02-1)
RN Q01-1 vs
RN Q02-1
MD Q01-1 vs
MD Q02-1
RN Q01-1 vs
MD Q01-1
RN Q02-1 vs
MD Q02-1
0%
0%
0%
3%
1.000
0.408
-
0.156
0.000
0.316
0.006
35%
1%
30%
0.000
0
0.000
0.200
48%
8%
25%
74%
0
0
0.000
0.000
0.008
0.725
61%
0.083
7%
0.000
Two-Sample t-test (CI 95%)
RN Q01-1 vs RN Q02-1
MD Q01-1 vs MD Q02-1
RN Q01-1 vs MD Q01-1
RN Q02-1 vs MD Q02-1
Not equal
(p value 0.0)
RN Q01-1 > RN Q02-1
Not equal
(p value 0.0)
MD Q01-1 > MD Q02-1
Not equal
(p value 0.0)
RN Q01-1 < MD Q01-1
Not equal
(p value 0.006)
RN Q02-1 < MD Q02-1
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
122
Response
Type
Two-proportions test (CI 95%)
Table 27: Results on 'Physician as Student' (Q01-2: Nurses can influence physicians' decisions patient care plan)
% Response
Never
Seldom
About Half the
time
Usually
Always
1%
17%
37%
MD
Perceived
(MD Q02-2)
0%
16%
41%
RN Q01-2
vs RN Q022
0.995
0.029
0.095
MD Q01-2
vs MD Q022
0.316
0.87
0.359
RN Q01-2
vs MD Q012
0.851
0.018
0.952
RN Q02-2
vs MD Q022
0.156
0.733
0.697
34%
11%
41%
2%
0.007
0.381
0.212
0
0.005
0.071
0.328
0.042
RN Actual
(RN Q012)
1%
9%
36%
RN Perceived
(RN Q02-2)
MD Actual
(MD Q01-2)
1%
15%
43%
47%
6%
36%
5%
Two-Sample t-test (CI 95%)
MD Q01-2 vs MD Q02-2
RN Q01-2 vs MD Q01-2
Equal
Equal
(p value 0.147)
(p value 0.275)
RN Q01-2 = MD Q01-2
MD Q01-2 = MD Q02-2
RN Q02-2 vs MD Q02-2
Equal
(p value 0.821)
RN Q02-2 = MD Q02-2
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
123
RN Q01-2 vs RN Q02-2
Not equal
(p value 0.002)
RN Q01-2 > RN Q02-2
Two-proportions test (CI 95%)
Table 28: Results on 'Collegial Relationship' (Q01-3: Physicians provide nurses appropriate authority regarding patient care)
% Response
Never
Seldom
About Half the
time
Usually
Always
RN Actual
(RN Q013)
1%
6%
22%
RN Perceived
(RN Q02-3)
MD Actual
(MD Q01-3)
1%
10%
37%
0%
1%
5%
56%
15%
45%
5%
53%
41%
MD
Perceived
(MD Q02-3)
0%
4%
39%
RN Q01-3
vs RN Q023
0.409
0.068
0.000
MD Q01-3
vs MD Q023
0.031
0.000
52%
0.007
0.793
5%
0.000
0.000
Two-Sample t-test (CI 95%)
MD Q01-3 vs MD Q02-3
RN Q01-3 vs MD Q01-3
Not Equal
Not Equal
(p value 0.00)
(p value 0.00)
MD Q01-3 > MD Q02-3
RN Q01-3 < MD Q01-3
RN Q01-3
vs MD Q013
0.156
0.000
0.000
RN Q02-3
vs MD Q023
0.004
0.688
0.507
0.000
0.160
0.769
RN Q02-3 vs MD Q02-3
Equal
(p value 0.02)
RN Q02-3 = MD Q02-3
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
124
RN Q01-3 vs RN Q02-3
Not equal
(p value 0.000)
RN Q01-3 > RN Q02-3
Two-proportions test (CI 95%)
Table 29: Results on 'Collegial Relationship' (Q01-5: Physicians are readily available to assist nurses with patient care)
% Response
Never
Seldom
About Half the
time
Usually
Always
RN Actual
(RN Q015)
9%
23%
28%
RN Perceived
(RN Q02-5)
MD Actual
(MD Q01-5)
13%
29%
28%
0%
4%
11%
31%
9%
25%
4%
48%
38%
MD
Perceived
(MD Q02-5)
1%
28%
34%
RN Q01-5
vs RN Q025
0.108
0.086
0.907
MD Q01-5
vs MD Q025
0.316
0.000
0.000
32%
0.102
0.002
4%
0.022
0.000
Two-Sample t-test (CI 95%)
MD Q01-5 vs MD Q02-5
RN Q01-5 vs MD Q01-5
Not Equal
Not Equal
(p value 0.001)
(p value 0.000)
MD Q01-5 > MD Q02-5
RN Q01-5 < MD Q01-5
RN Q01-5
vs MD Q015
0.000
0.000
0.000
RN Q02-5
vs MD Q025
0.000
0.858
0.181
0.000
0.000
0.081
0.095
RN Q02-5 vs MD Q02-5
Not Equal
(p value 0.000)
RN Q02-5 < MD Q02-5
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
125
RN Q01-5 vs RN Q02-5
Not equal
(p value 0.001)
RN Q01-5 > RN Q02-5
Two-proportions test (CI 95%)
Table 30: Results on 'Collaborative Relationship' (Q01-4: Physicians and RNs discuss together to develop care plan)
% Response
Never
Seldom
About Half the
time
Usually
Always
RN Actual
(RN Q014)
5%
28%
23%
RN Perceived
(RN Q02-4)
MD Actual
(MD Q01-4)
4%
23%
41%
1%
20%
18%
34%
10%
28%
2%
41%
20%
MD
Perceived
(MD Q02-4)
0%
32%
43%
RN Q01-4
vs RN Q024
0.879
0.194
0.000
MD Q01-4
vs MD Q024
0.316
0.007
0.000
23%
0.119
0.000
2%
0.000
0.000
Two-Sample t-test (CI 95%)
MD Q01-4 vs MD Q02-4
RN Q01-4 vs MD Q01-4
Not Equal
Not Equal
(p value 0.000)
(p value 0.000)
MD Q01-4 > MD Q02-4
RN Q01-4 < MD Q01-4
RN Q01-4
vs MD Q014
0.002
0.041
0.168
RN Q02-4
vs MD Q024
0.000
0.036
0.758
0.099
0.004
0.213
0.538
RN Q02-4 vs MD Q02-4
Equal
(p value 0.396)
RN Q02-4 = MD Q02-4
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
126
RN Q01-4 vs RN Q02-4
Not equal
(p value 0.049)
RN Q01-4 > RN Q02-4
Two-proportions test (CI 95%)
Table 31: Table 11: Results on 'Collaborative Relationship' (Q01-6: Physicians are always in charge in deciding care plan)
% Response
Never
Seldom
About Half the
time
Usually
Always
RN Actual
(RN Q016)
2%
16%
32%
RN Perceived
(RN Q02-6)
MD Actual
(MD Q01-6)
1%
17%
29%
1%
4%
4%
40%
9%
44%
9%
47%
43%
MD
Perceived
(MD Q02-6)
0%
3%
11%
RN Q01-6
vs RN Q026
0.203
0.811
0.436
MD Q01-6
vs MD Q026
0.155
0.763
0.006
55%
0.340
0.145
30%
0.898
0.007
Two-Sample t-test (CI 95%)
MD Q01-6 vs MD Q02-6
RN Q01-6 vs MD Q01-6
Not Equal
Not Equal
(p value 0.040)
(p value 0.000)
MD Q01-6 > MD Q02-6
RN Q01-6 < MD Q01-6
RN Q01-6
vs MD Q016
0.272
0.000
0.000
RN Q02-6
vs MD Q026
0.082
0.000
0.000
0.093
0.000
0.013
0.000
RN Q02-6 vs MD Q02-6
Not Equal
(p value 0.000)
RN Q02-6 < MD Q02-6
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
127
RN Q01-6 vs RN Q02-6
Equal
(p value 0.495)
RN Q01-6 = RN Q02-6
Two-proportions test (CI 95%)
Table 32: Results on Hostile/adversarial Relationship (Q01-7: RNs are frustrated with their interaction to physicians)
% Response
Never
Seldom
About Half the
time
Usually
Always
RN Actual
(RN Q017)
7%
65%
23%
RN Perceived
(RN Q02-7)
MD Actual
(MD Q01-7)
2%
42%
42%
16%
80%
2%
5%
0%
13%
1%
1%
1%
MD
Perceived
(MD Q02-7)
2%
57%
35%
RN Q01-7
vs RN Q027
0.002
0.000
0.000
MD Q01-7
vs MD Q027
0
0.000
0.000
5%
0.000
0.018
1%
0.044
0.997
Two-Sample t-test (CI 95%)
MD Q01-7 vs MD Q02-7
RN Q01-7 vs MD Q01-7
Not Equal
Not Equal
(p value 0.000)
(p value 0.000)
MD Q01-7 < MD Q02-7
RN Q01-7 > MD Q01-7
RN Q01-7
vs MD Q017
0.002
0.000
0.000
RN Q02-7
vs MD Q027
0.945
0.001
0.129
0.004
0.316
0.003
0.754
RN Q02-7 vs MD Q02-7
Not Equal
(p value 0.000)
RN Q02-7 > MD Q02-7
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
128
RN Q01-7 vs RN Q02-7
Not Equal
(p value 0.000)
RN Q01-7 < RN Q02-7
Two-proportions test (CI 95%)
Table 33: Results on Hostile/adversarial Relationship (Q01-8: Physicians act in a domineering way toward nurses)
% Response
Never
Seldom
About Half the
time
Usually
Always
RN Actual
(RN Q018)
17%
54%
21%
RN Perceived
(RN Q02-8)
6%
47%
32%
MD Actual
(MD Q018)
58%
39%
2%
7%
0%
14%
1%
1%
0%
MD Perceived
(MD Q02-8)
3%
51%
37%
RN Q01-8
vs RN Q028
0.000
0.069
0.002
MD Q01-8
vs MD Q028
0
0.021
0.000
10%
0.011
0.000
0%
0.177
1.000
Two-Sample t-test (CI 95%)
MD Q01-8 vs MD Q02-8
RN Q01-8 vs MD Q01-8
Not Equal
Not Equal
(p value 0.000)
(p value 0.000)
MD Q01-8 < MD Q02-8
RN Q01-8 > MD Q01-8
RN Q01-8
vs MD Q018
0.000
0.001
0.000
RN Q02-8
vs MD Q028
0.176
0.422
0.328
0.001
0.316
0.154
-
RN Q02-8 vs MD Q02-8
Equal
(p value 0.436)
RN Q02-8 = MD Q02-8
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
129
RN Q01-8 vs RN Q02-8
Not Equal
(p value 0.000)
RN Q01-8 < RN Q02-8
Two-proportions test (CI 95%)
Table 34: Results on formal relationship (Q01-9: Nurses interactions with physician is formal)
% Response
RN Actual
(RN Q01-9)
Two-proportions test (CI 95%)
1%
RN Q01-9
vs RN Q029
0.529
MD Q01-9
vs MD Q029
0.01
RN Q01-9
vs MD Q019
0.469
RN Q02-9
vs MD Q029
0.074
MD Actual
(MD Q019)
6%
MD Perceived
(MD Q02-9)
Never
4%
RN
Perceived
(RN Q02-9)
3%
Seldom
25%
25%
46%
24%
0.868
0.000
0.000
0.785
About Half the
time
Usually
43%
42%
37%
49%
0.830
0.021
0.187
0.120
24%
27%
9%
26%
0.384
0.000
0.000
0.751
Always
3%
3%
2%
1%
0.637
-
0.411
-
RN Q01-9 vs RN Q02-9
MD Q01-9 vs MD Q02-9
RN Q01-9 vs MD Q01-9
RN Q02-9 vs MD Q02-9
Equal
(p value 0.548)
RN Q01-9 = RN Q02-9
Not Equal
(p value 0.000)
MD Q01-9 < MD Q02-9
Not Equal
(p value 0.000)
RN Q01-9 > MD Q01-9
Equal
(p value 0.970)
RN Q02-9 = MD Q02-9
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
130
Two-Sample t-test (CI 95%)
Table 35: Results on formal relationship (Q01-10: Physicians expect nurses’ role to answer their questions about patients)
% Response
RN Actual
(RN Q0110)
Two-proportions test (CI 95%)
RN
Perceived
(RN Q02-10)
MD Actual
(MD Q01-10)
MD Perceived
(MD Q02-10)
RN Q01-10
vs RN Q0210
MD Q01-10
vs MD Q0210
RN Q01-10 vs
MD Q01-10
RN Q02-10 vs
MD Q02-10
Never
9%
4%
35%
5%
0.019
0
0.000
0.526
Seldom
34%
25%
43%
31%
0.013
0.013
0.065
0.202
About Half
the time
Usually
34%
38%
18%
41%
0.275
0.000
0.000
0.617
21%
30%
4%
22%
0.000
0.000
0.000
0.040
Always
1%
2%
0%
1%
0.729
-
-
0.555
131
Two-Sample t-test (CI 95%)
RN Q01-10 vs RN Q02-10
MD Q01-10 vs MD Q02-10
RN Q01-10 vs MD Q01-10
RN Q02-10 vs MD Q02-10
Not Equal
(p value 0.0)
RN Q01-10 < RN Q02-10
Not Equal
(p value 0.000)
MD Q01-10 < MD Q02-10
Not Equal
(p value 0.000)
RN Q01-10 > MD Q01-10
Not Equal
(p value 0.034)
RN Q02-10 > MD Q02-10
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
Appendix F2: Results of Actual vs Perceived Norms of Relationship Nature (Injunctive)
Table 36: Results on 'Physician as teacher' (Q03-1: Physicians should be willing to explain issues regarding patient care to
nurses)
% Response
RN
Two-proportions test (CI 95%)
Descriptive vs
Injunctive Norms
Injunctive
MD
RN
ActualI (RN
Q03-1)
RN
Perceived
-I (RN
Q04-1)
MD
ActualD (MD
Q01-1)
MD
ActualI (MD
Q03-1)
MD
Perceived
-I (MD
Q04-1)
RN
Q01-1
vs RN
Q03-1
MD
Q01-1
vs MD
Q03-1
RN
Q03-1
vs RN
Q04-1
MD
Q03-1
vs MD
Q04-1
RN
Q03-1
vs MD
Q03-1
RN
Q04-1
vs MD
Q04-1
1%
0%
0%
0%
1%
0%
-
-
-
-
-
-
6%
1%
1%
0%
0%
2%
0.000
-
-
-
-
-
Neutral
17%
1%
1%
1%
1%
7%
0.000
-
-
0.001
-
0.002
Agree
Strongly
Agree
56%
22%
26%
25%
25%
60%
0.000
1.000
0.269
0.000
0.508
0.000
20%
76%
72%
74%
74%
31%
0.000
1.000
0.240
0.000
0.563
0.000
Strongly
Disagree
Disagree
RN Q01-1 vs RN
Q03-1
MD Q01-1 vs MD
Q03-1
Two-Sample t-test (CI 95%)
RN Q03-1 vs RN
MD Q03-1 vs MD
Q04-1
Q04-1
RN Q03-1 vs MD
Q03-1
RN Q04-1 vs MD
Q04-1
Not equal
(p value 0.000)
RN Q01-1 < RN
Q03-1
Equal
(p value 0.582)
MD Q01-1 = MD
Q03-1
Equal
(p value 0.375)
RN Q03-1 = RN
Q04-1
Equal
(p value 0.769)
RN Q03-1 = MD
Q03-1
Not Equal
(p value 0.000)
RN Q04-1 > MD
Q04-1
Not Equal
(p value 0.000)
MD Q03-1 > MD
Q04-1
Note 1: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
Note 2: I - Injunctive Norms, D - Descriptive Norms
133
RN
ActualD
(RN
Q01-1)
Table 37: Results on 'Physician as teacher' (Q03-2)
% Response
RN
Two-proportions test (CI 95%)
MD
Descriptive vs
Injunctive
RN
MD
Q01-2
Q01-2
vs RN
vs MD
Q03-2
Q03-2
RN
ActualI (RN
Q03-2)
RN
Perceived
-I (RN
Q04-2)
MD
ActualD (MD
Q01-2)
MD
ActualI (MD
Q03-2)
MD
Perceived
-I (MD
Q04-2)
0%
0%
1%
1%
1%
-
9%
0%
0%
17%
2%
11%
Neutral
36%
6%
5%
37%
8%
Agree
47%
44%
45%
34%
Strongly
Agree
6%
50%
50%
11%
Strongly
Disagree
Disagree
RN
Q03-2
vs RN
Q04-2
MD
Q03-2
vs MD
Q04-2
RN
Q03-2
vs MD
Q03-2
RN
Q04-2
vs MD
Q04-2
-
-
-
-
-
0.000
0.000
-
0.000
-
0.000
23%
0.000
0.000
0.492
0.000
0.645
0.000
53%
53%
0.364
0.001
0.747
1.000
0.051
0.095
37%
12%
0.000
0.000
1.000
0.000
0.006
0.000
Two-Sample t-test (CI 95%)
RN Q01-2 vs RN
Q03-2
Not equal
(p value 0.000)
RN Q01-2 < RN
Q03-2
MD Q01-2 vs MD
Q03-2
Not Equal
(p value 0.00)
MD Q01-2 < MD
Q03-2
RN Q03-2 vs RN
Q04-2
Equal
(p value 0.851)
RN Q03-2 = RN
Q04-2
MD Q03-2 vs MD
Q04-2
Not Equal
(p value 0.001)
MD Q03-2 > MD
Q04-2
RN Q03-2 vs MD
Q03-2
Not Equal
(p value 0.004)
RN Q03-2 > MD
Q03-2
RN Q04-2 vs MD
Q04-2
Not Equal
(p value 0.000)
RN Q04-2 > MD
Q04-2
Note 1: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate
hypothesis.
Note 2: I - Injunctive Norms, D - Descriptive Norms
133
RN
ActualD
(RN
Q01-2)
1%
Injunctive Norms
Table 38: Results on 'Collegial Relationship' (Q03-3)
% Response
RN
Strongly
Disagree
Disagree
Neutral
Two-proportions test (CI 95%)
MD
Descriptive vs
Injunctive
RN
MD
Q01-3
Q01-3
vs RN
vs MD
Q03-3
Q03-3
RN
ActualD
(RN
Q01-3)
1%
RN
ActualI (RN
Q03-3)
RN
Perceived
-I (RN
Q04-3)
MD
ActualD (MD
Q01-3)
MD
ActualI (MD
Q03-3)
MD
Perceived
-I (MD
Q04-3)
0%
1%
0%
1%
1%
-
6%
0%
0%
1%
2%
5%
22%
4%
5%
5%
6%
18%
Injunctive Norms
RN
Q03-3
vs RN
Q04-3
MD
Q03-3
vs MD
Q04-3
RN
Q03-3
vs MD
Q03-3
RN
Q04-3
vs MD
Q04-3
-
-
-
-
-
0.000
-
-
0.047
-
0.001
0.000
0.654
0.675
0.000
0.370
0.005
56%
47%
46%
53%
51%
62%
0.021
0.638
0.742
0.035
0.379
0.000
15%
49%
49%
41%
41%
15%
0.000
1.000
0.999
0.000
0.079
0.000
Two-Sample t-test (CI 95%)
RN Q01-3 vs RN
Q03-3
Not equal
(p value 0.000)
RN Q01-3 < RN
Q03-3
MD Q01-3 vs MD
Q03-3
Equal
(p value 0.459)
MD Q01-3 = MD
Q03-3
RN Q03-3 vs RN
Q04-3
Equal
(p value 0.585)
RN Q03-3 = RN
Q04-3
MD Q03-3 vs MD
Q04-3
Not Equal
(p value 0.016)
MD Q03-3 > MD
Q04-3
RN Q03-3 vs MD
Q03-3
Not Equal
(p value 0.000)
RN Q03-3 > MD
Q03-3
Note 1: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
Note 2: I - Injunctive Norms, D - Descriptive Norms
RN Q04-3 vs MD
Q04-3
Not Equal
(p value 0.000)
RN Q04-3 > MD
Q04-3
134
Agree
Strongly
Agree
Table 39: Results on 'Collegial Relationship' (Q03-5)
% Response
RN
Two-proportions test (CI 95%)
MD
Descriptive vs
Injunctive
RN
MD
Q01-5
Q01-5
vs RN
vs MD
Q03-5
Q03-5
Injunctive Norms
RN
Q03-5
vs RN
Q04-5
MD
Q03-5
vs MD
Q04-5
RN
Q03-5
vs MD
Q03-5
RN
Q04-5
vs MD
Q04-5
RN
ActualI (RN
Q03-5)
RN
Perceived
-I (RN
Q04-5)
MD
ActualD (MD
Q01-5)
MD
ActualI (MD
Q03-5)
MD
Perceived
-I (MD
Q04-5)
1%
2%
0%
1%
2%
0.000
-
0.468
-
-
0.944
23%
7%
7%
4%
4%
10%
0.000
0.792
0.973
0.185
0.185
0.249
Neutral
28%
23%
21%
11%
17%
30%
0.124
0.096
0.665
0.002
0.103
0.028
Agree
31%
39%
36%
48%
47%
42%
0.040
0.917
0.449
0.317
0.087
0.207
Strongly
Agree
9%
30%
34%
38%
32%
16%
0.000
0.276
0.333
0.000
0.762
0.000
Strongly
Disagree
Disagree
Two-Sample t-test (CI 95%)
RN Q01-5 vs RN
MD Q01-5 vs MD
RN Q03-5 vs RN
MD Q03-5 vs MD
RN Q03-5 vs MD
RN Q04-5 vs MD
Q03-5
Q03-5
Q04-5
Q04-5
Q03-5
Q04-5
Equal
Equal
Equal
Not equal
Not Equal
Not Equal
(p value 0.000)
(p value 0.084)
(p value 0.711)
(p value 0.000)
(p value 0.084)
(p value 0.000)
RN Q01-5 < RN
MD Q01-5 = MD
RN Q03-5 = RN
MD Q03-5 > MD
RN Q03-5 = MD
RN Q04-5 > MD
Q03-5
Q03-5
Q04-5
Q04-5
Q03-5
Q04-5
Note 1: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
Note 2: I - Injunctive Norms, D - Descriptive Norms
135
RN
ActualD
(RN
Q01-5)
9%
Table 40: Results on 'Collaborative Relationship' (Q03-4)
% Response
RN
Strongly
Disagree
Disagree
Neutral
Two-proportions test (CI 95%)
MD
Descriptive vs
Injunctive
RN
MD
Q01-4
Q01-4
vs RN
vs MD
Q03-4
Q03-4
RN
ActualD
(RN
Q01-4)
5%
RN
ActualI (RN
Q03-4)
RN
Perceived
-I (RN
Q04-4)
MD
ActualD (MD
Q01-4)
MD
ActualI (MD
Q03-4)
MD
Perceived
-I (MD
Q04-4)
0%
0%
1%
1%
1%
-
28%
0%
1%
20%
3%
12%
23%
4%
8%
18%
13%
33%
Injunctive Norms
RN
Q03-4
vs RN
Q04-4
MD
Q03-4
vs MD
Q04-4
RN
Q03-4
vs MD
Q03-4
RN
Q04-4
vs MD
Q04-4
-
-
-
-
-
0.000
0.000
-
0.001
-
0.000
0.000
0.198
0.052
0.008
0.001
0.000
34%
37%
40%
41%
47%
42%
0.548
0.347
0.362
0.347
0.031
0.752
10%
59%
51%
20%
37%
12%
0.000
0.000
0.047
0.000
0.000
0.000
Two-Sample t-test (CI 95%)
RN Q01-4 vs RN
Q03-4
Not equal
(p value 0.000)
RN Q01-4 < RN
Q03-4
MD Q01-4 vs MD
Q03-4
Not Equal
(p value 0.000)
MD Q01-4 < MD
Q03-4
RN Q03-4 vs RN
Q04-4
Not Equal
(p value 0.000)
RN Q03-4 > RN
Q04-4
MD Q03-4 vs MD
Q04-4
Not Equal
(p value 0.000)
MD Q03-4 > MD
Q04-4
RN Q03-4 vs MD
Q03-4
Not Equal
(p value 0.000)
RN Q03-4 > MD
Q03-4
Note 1: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
Note 2: I - Injunctive Norms, D - Descriptive Norms
RN Q04-4 vs MD
Q04-4
Not Equal
(p value 0.000)
RN Q04-4 > MD
Q04-4
136
Agree
Strongly
Agree
Table 41: Results on Collaborative Relationship (Q03-6)
% Response
RN
Two-proportions test (CI 95%)
MD
Descriptive vs
Injunctive
RN
MD
Q01-6
Q01-6
vs RN
vs MD
Q03-6
Q03-6
Injunctive Norms
RN
Q03-6
vs RN
Q04-6
MD
Q03-6
vs MD
Q04-6
RN
Q03-6
vs MD
Q03-6
RN
Q04-6
vs MD
Q04-6
RN
ActualI (RN
Q03-6)
RN
Perceived
-I (RN
Q04-6)
MD
ActualD (MD
Q01-6)
MD
ActualI (MD
Q03-6)
MD
Perceived
-I (MD
Q04-6)
8%
12%
1%
2%
1%
0.001
0.661
0.129
-
0.001
0.000
16%
35%
31%
4%
8%
4%
0.000
0.120
0.242
0.186
0.000
0.000
Neutral
32%
27%
26%
4%
13%
18%
0.196
0.001
0.818
0.252
0.000
0.026
Agree
40%
24%
25%
47%
44%
45%
0.000
0.476
0.887
0.835
0.000
0.000
Strongly
Agree
9%
5%
6%
43%
33%
32%
0.038
0.044
0.577
0.825
0.000
0.000
Strongly
Disagree
Disagree
Two-Sample t-test (CI 95%)
RN Q01-6 vs RN
Q03-6
Not equal
(p value 0.000)
RN Q01-6 > RN
Q03-6
MD Q01-6 vs MD
Q03-6
Not Equal
(p value 0.002)
MD Q01-6 > MD
Q03-6
RN Q03-6 vs RN
Q04-6
Equal
(p value 0.959)
RN Q03-6 = RN
Q04-6
MD Q03-6 vs MD
Q04-6
Equal
(p value 0.647)
MD Q03-6 = MD
Q04-6
RN Q03-6 vs MD
Q03-6
Not Equal
(p value 0.000)
RN Q03-6 < MD
Q03-6
Note 1: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
Note 2: I - Injunctive Norms, D - Descriptive Norms
RN Q04-6 vs MD
Q04-6
Not Equal
(p value 0.000)
RN Q04-6 < MD
Q04-6
137
RN
ActualD
(RN
Q01-6)
2%
Table 42: Results on 'Hostile/adversarial Relationship' (Q03-7)
% Response
RN
Strongly
Disagree
Disagree
Neutral
Two-proportions test (CI 95%)
MD
Descriptive vs
Injunctive
RN
MD
Q01-7
Q01-7
vs RN
vs MD
Q03-7
Q03-7
Injunctive Norms
RN
Q03-7
vs RN
Q04-7
MD
Q03-7
vs MD
Q04-7
RN
Q03-7
vs MD
Q03-7
RN
Q04-7
vs MD
Q04-7
RN
ActualD
(RN
Q01-7)
7%
RN
ActualI (RN
Q03-7)
RN
Perceived
-I (RN
Q04-7)
MD
ActualD (MD
Q01-7)
MD
ActualI (MD
Q03-7)
MD
Perceived
-I (MD
Q04-7)
85%
84%
16%
81%
62%
0.000
0.000
0.793
0.000
0.235
0.000
65%
14%
15%
80%
18%
32%
0.000
0.000
0.788
0.002
0.249
0.000
23%
0%
0%
2%
1%
3%
0.000
0.410
-
0.153
-
0.030
5%
1%
0%
1%
0%
3%
0.002
-
-
-
-
-
0%
0%
1%
1%
1%
1%
-
-
-
-
-
-
Two-Sample t-test (CI 95%)
RN Q01-7 vs RN
Q03-7
Not equal
(p value 0.000)
RN Q01-7 > RN
Q03-7
MD Q01-7 vs MD
Q03-7
Not Equal
(p value 0.000)
MD Q01-7 > MD
Q03-7
RN Q03-7 vs RN
Q04-7
Equal
(p value 0.789)
RN Q03-7 = RN
Q04-7
MD Q03-7 vs MD
Q04-7
Not Equal
(p value 0.000)
MD Q03-7 < MD
Q04-7
RN Q03-7 vs MD
Q03-7
Equal
(p value 0.410)
RN Q03-7 = MD
Q03-7
Note 1: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
Note 2: I - Injunctive Norms, D - Descriptive Norms
RN Q04-7 vs MD
Q04-7
Not Equal
(p value 0.000)
RN Q04-7 < MD
Q04-7
138
Agree
Strongly
Agree
Table 43: Results on 'Hostile/adversarial Relationship' (Q03-8)
% Response
RN
Strongly
Disagree
Disagree
Neutral
Two-proportions test (CI 95%)
MD
Descriptive vs
Injunctive
RN
MD
Q01-8
Q01-8
vs RN
vs MD
Q03-8
Q03-8
Injunctive Norms
RN
Q03-8
vs RN
Q04-8
MD
Q03-8
vs MD
Q04-8
RN
Q03-8
vs MD
Q03-8
RN
Q04-8
vs MD
Q04-8
RN
ActualD
(RN
Q01-8)
17%
RN
ActualI (RN
Q03-8)
RN
Perceived
-I (RN
Q04-8)
MD
ActualD (MD
Q01-8)
MD
ActualI (MD
Q03-8)
MD
Perceived
-I (MD
Q04-8)
88%
87%
58%
83%
55%
0.000
0.000
0.685
0.000
0.108
0.000
54%
10%
12%
39%
14%
35%
0.000
0.000
0.487
0.000
0.174
0.000
21%
0%
1%
2%
3%
8%
0.000
0.736
0.313
0.033
0.057
0.001
7%
1%
0%
1%
0%
2%
0.000
-
0.318
-
-
-
0%
1%
0%
0%
1%
1%
-
-
-
-
-
-
Two-Sample t-test (CI 95%)
RN Q01-8 vs RN
Q03-8
Not equal
(p value 0.000)
RN Q01-8 > RN
Q03-8
MD Q01-8 vs MD
Q03-8
Not Equal
(p value 0.000)
MD Q01-8 > MD
Q03-8
RN Q03-8 vs RN
Q04-8
Equal
(p value 0.684)
RN Q03-8 = RN
Q04-8
MD Q03-8 vs MD
Q04-8
Not Equal
(p value 0.000)
MD Q03-8 < MD
Q04-8
RN Q03-8 vs MD
Q03-8
Equal
(p value 0.292)
RN Q03-8 = MD
Q03-8
Note 1: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
Note 2: I - Injunctive Norms, D - Descriptive Norms
RN Q04-8 vs MD
Q04-8
Not Equal
(p value 0.000)
RN Q04-8 < MD
Q04-8
139
Agree
Strongly
Agree
Table 44: Results on 'Formal Relationship' (Q03-9)
% Response
RN
Two-proportions test (CI 95%)
MD
Descriptive vs
Injunctive
RN
MD
Q01-9
Q01-9
vs RN
vs MD
Q03-9
Q03-9
Injunctive Norms
RN
Q03-9
vs RN
Q04-9
MD
Q03-9
vs MD
Q04-9
RN
Q03-9
vs MD
Q03-9
RN
Q04-9
vs MD
Q04-9
RN
ActualI (RN
Q03-9)
RN
Perceived
-I (RN
Q04-9)
MD
ActualD (MD
Q01-9)
MD
ActualI (MD
Q03-9)
MD
Perceived
-I (MD
Q04-9)
18%
23%
6%
13%
4%
0.000
0.020
0.132
0.003
0.158
0.000
25%
33%
33%
46%
33%
24%
0.047
0.010
0.930
0.038
0.958
0.019
Neutral
43%
30%
28%
37%
40%
49%
0.003
0.522
0.580
0.075
0.036
0.000
Agree
24%
18%
14%
9%
13%
22%
0.055
0.246
0.156
0.019
0.132
0.021
Strongly
Agree
3%
1%
2%
2%
1%
1%
0.049
0.410
0.307
-
-
0.386
Strongly
Disagree
Disagree
Two-Sample t-test (CI 95%)
RN Q01-9 vs RN
Q03-9
Not equal
(p value 0.000)
RN Q01-9 > RN
Q03-9
MD Q01-9 vs MD
Q03-9
Equal
(p value 0.952)
MD Q01-9 = MD
Q03-9
RN Q03-9 vs RN
Q04-9
Equal
(p value 0.142)
RN Q03-9 = RN
Q04-9
MD Q03-9 vs MD
Q04-9
Not Equal
(p value 0.000)
MD Q03-9 < MD
Q04-9
RN Q03-9 vs MD
Q03-9
Equal
(p value 0.635)
RN Q03-9 = MD
Q03-9
Note 1: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
Note 2: I - Injunctive Norms, D - Descriptive Norms
RN Q04-9 vs MD
Q04-9
Not Equal
(p value 0.000)
RN Q04-9 < MD
Q04-9
140
RN
ActualD
(RN
Q01-9)
4%
Table 45: Results on 'Formal Relationship' (Q03-10)
% Response
RN
MD
RN
ActualI (RN
Q0310)
36%
RN
Perceived
-I (RN
Q04-10)
MD
ActualD (MD
Q01-10)
39%
34%
48%
Neutral
34%
14%
Agree
21%
2%
2%
Strongly
Agree
1%
0%
0%
Descriptive vs
Injunctive
RN
MD
Q01-10 Q01-10
vs RN
vs MD
Q03-10 Q03-10
MD
Perceived
-I (MD
Q04-10)
35%
MD
ActualI (MD
Q0310)
28%
12%
0.000
40%
43%
52%
38%
19%
18%
16%
4%
0%
Injunctive Norms
RN
Q03-10
vs RN
Q04-10
MD
Q03-10
vs MD
Q04-10
RN
Q03-10
vs MD
Q03-10
RN
Q04-10
vs MD
Q04-10
0.145
0.602
0.000
0.048
0.000
0.001
0.076
0.071
0.006
0.334
0.646
37%
0.000
0.588
0.133
0.000
0.565
0.000
3%
10%
0.000
0.557
0.548
0.003
0.476
0.000
1%
3%
-
-
-
0.251
-
-
Two-Sample t-test (CI 95%)
RN Q01-10 vs RN
Q03-10
Not equal
(p value 0.000)
RN Q01-10 > RN
Q03-10
MD Q01-10 vs MD
Q03-10
Equal
(p value 0.484)
MD Q01-10 = MD
Q03-10
RN Q03-10 vs RN
Q04-10
Equal
(p value 0.539)
RN Q03-10 = RN
Q04-10
MD Q03-10 vs MD
Q04-10
Not Equal
(p value 0.000)
MD Q03-10 < MD
Q04-10
RN Q03-10 vs MD
Q03-10
Not Equal
(p value 0.032)
RN Q03-10 < MD
Q03-10
Note 1: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
Note 2: I - Injunctive Norms, D - Descriptive Norms
RN Q04-10 vs MD
Q04-10
Not Equal
(p value 0.000)
RN Q04-10 < MD
Q04-10
141
RN
ActualD
(RN
Q01-10)
9%
Strongly
Disagree
Disagree
Two-proportions test (CI 95%)
APPENDIX F3: RESULTS OF ACTUAL VS PERCEIVED NORMS OF SUPPORTIVE PHYSICIAN BEHAVIORS
Table 46: Results on supportive Physician Behavior (Q05-1) - Cooperative behavior toward nurses
% Response
RN
MD Response
Response
RN Actual
(RN Q051)
RN
Perceived
(RN Q07-1)
Two-proportions test (CI 95%)
MD
Perceived
(MD Q07-1)
RN Q05-1
vs RN
Q07-1
MD Q05-1
vs MD
Q07-1
RN Q05-1
vs MD
Q05-1
0%
-
-
-
RN Q07-1
vs MD
Q07-1
None
Never
0%
0%
MD
Actual
(MD
Q05-1)
0%
Few
Seldom
3%
7%
0%
2%
0.020
-
-
0.003
Some
7%
31%
0%
19%
0.000
0
0.000
0.002
Most
About Half the
time
Usually
69%
55%
53%
76%
0.001
0
0.000
0.000
Everyone
Always
21%
7%
47%
4%
0.000
0
0.000
0.076
-
RN Q05-1 vs RN Q07-1
MD Q05-1 vs MD Q07-1
RN Q05-1 vs MD Q05-1
RN Q07-1 vs MD Q07-1
Not equal
(p value 0.000)
RN Q05-1 > RN Q07-1
Not Equal
(p value 0.000)
MD Q05-1 > MD Q07-1
Not Equal
(p value 0.000)
RN Q05-1 < MD Q05-1
Not Equal
(p value 0.001)
RN Q07-1 < MD Q07-1
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate
hypothesis.
142
Two-Sample t-test (CI 95%)
Table 47: Results on Supportive Physician Behavior (Q05-2) - Correct in a supporting manner
% Response
RN
MD Response
Response
RN Actual
(RN Q052)
RN
Perceived
(RN Q07-2)
Two-proportions test (CI 95%)
MD
Perceived
(MD Q07-2)
RN Q05-2
vs RN
Q07-2
MD Q05-2
vs MD
Q07-2
RN Q05-2
vs MD
Q05-2
0%
0.043
-
-
RN Q07-2
vs MD
Q07-2
None
Never
5%
2%
MD
Actual
(MD
Q05-2)
1%
Few
Seldom
11%
15%
2%
6%
0.194
-
0.000
0.002
Some
18%
39%
6%
37%
0.000
0
0.000
0.645
Most
About Half the
time
Usually
49%
37%
57%
53%
0.005
0.431
0.101
0.001
Everyone
Always
16%
7%
34%
4%
0.000
0
0.000
0.138
-
143
Two-Sample t-test (CI 95%)
RN Q05-2 vs RN Q07-2
MD Q05-2 vs MD Q07-2
RN Q05-2 vs MD Q05-2
RN Q07-2 vs MD Q07-2
Not equal
(p value 0.000)
RN Q05-2 > RN Q07-2
Not Equal
(p value 0.000)
MD Q05-2 > MD Q07-2
Not Equal
(p value 0.000)
RN Q05-2 < MD Q05-2
Not Equal
(p value 0.002)
RN Q07-2 < MD Q07-2
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate
hypothesis.
Table 48: Results on Supportive Physician Behavior (Q05-3) - Act supportive when stressed
% Response
Two-proportions test (CI 95%)
MD
Perceived
(MD Q07-3)
RN Q05-3
vs RN
Q07-3
MD Q05-3
vs MD
Q07-3
RN Q05-3
vs MD
Q05-3
0%
0.591
-
0.000
RN Q07-3
vs MD
Q07-3
None
Never
6%
5%
MD
Actual
(MD
Q05-3)
0%
Few
Seldom
16%
22%
2%
11%
0.092
0
0.000
0.001
Some
28%
37%
7%
36%
0.013
0
0.000
0.779
Most
About Half the
time
Usually
37%
30%
62%
52%
0.096
0.046
0.000
0.000
Everyone
Always
13%
6%
30%
2%
0.002
0
0.000
0.011
RN
MD Response
Response
RN Actual
(RN Q053)
RN
Perceived
(RN Q07-3)
0
RN Q05-3 vs RN Q07-3
MD Q05-3 vs MD Q07-3
RN Q05-3 vs MD Q05-3
RN Q07-3 vs MD Q07-3
Not equal
(p value 0.004)
RN Q05-3 > RN Q07-3
Not Equal
(p value 0.000)
MD Q05-3 > MD Q07-3
Not Equal
(p value 0.000)
RN Q05-3 < MD Q05-3
Not Equal
(p value 0.000)
RN Q07-3 < MD Q07-3
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate
hypothesis.
144
Two-Sample t-test (CI 95%)
Table 49: Results on Supportive Physician Behavior (Q05-4) - Responsive timely
% Response
RN
MD Response
Response
RN Actual
(RN Q054)
RN
Perceived
(RN Q07-4)
MD
Actual
(MD
Q05-4)
Two-proportions test (CI 95%)
MD
Perceived
(MD Q07-4)
RN Q05-4
vs RN
Q07-4
MD Q05-4
vs MD
Q07-4
RN Q05-4
vs MD
Q05-4
RN Q07-4
vs MD
Q07-4
Never
1%
1%
0%
0%
0.651
-
-
-
Few
Seldom
7%
13%
1%
5%
0.030
-
0.000
0.001
Some
24%
39%
4%
30%
0.000
0
0.000
0.034
Most
About Half the
time
Usually
53%
41%
56%
62%
0.002
0.245
0.487
0.000
Everyone
Always
15%
8%
38%
3%
0.006
0
0.000
0.036
Two-Sample t-test (CI 95%)
RN Q05-4 vs RN Q07-4
MD Q05-4 vs MD Q07-4
RN Q05-4 vs MD Q05-4
RN Q07-4 vs MD Q07-4
Not equal
(p value 0.000)
RN Q05-4 > RN Q07-4
Not Equal
(p value 0.000)
MD Q05-4 > MD Q07-4
Not Equal
(p value 0.000)
RN Q05-4 < MD Q05-4
Not Equal
(p value 0.000)
RN Q07-4 < MD Q07-4
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate
hypothesis.
145
None
Table 50: Results on Impact of Supportive Physician Behavior (Q06-1) - Reduces delays in care
% Response
Strongly Disagree
Disagree
Neutral
Agree
Strongly Agree
RN Actual
(RN Q06-1)
RN Perceived
(RN Q08-1)
MD Actual
(MD Q061)
1%
6%
8%
51%
33%
0%
6%
12%
53%
29%
0%
1%
11%
51%
37%
MD Perceived
(MD Q08-1)
RN Q06-1
vs RN Q081
MD Q06-1
vs MD Q081
1%
0.177
5%
0.862
16%
0.173
0.18
63%
0.742
0.013
15%
0.374
0
Two-Sample t-test (CI 95%)
MD Q06-1 vs MD Q08-1
RN Q06-1 vs MD Q06-1
Not Equal
Not Equal
(p value 0.000)
(p value 0.035)
MD Q06-1 > MD Q08-1
RN Q06-1 < MD Q06-1
RN Q06-1
vs MD
Q06-1
0.002
0.297
0.863
0.374
RN Q08-1
vs MD Q081
0.75
0.673
0.183
0.026
0.000
RN Q08-1 vs MD Q08-1
Not Equal
(p value 0.018)
RN Q08-1 > MD Q08-1
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
146
RN Q06-1 vs RN Q08-1
Equal
(p value 0.000)
RN Q06-1 = RN Q08-1
Two-proportions test (CI 95%)
Table 51: Results on Impact of Supportive Physician Behavior (Q06-2) - Reduces medical error
% Response
Strongly Disagree
Disagree
Neutral
Agree
Strongly Agree
RN Actual
(RN Q06-2)
RN Perceived
(RN Q08-2)
MD Actual
(MD Q062)
1%
6%
16%
45%
32%
1%
6%
16%
47%
29%
0%
1%
10%
56%
34%
MD Perceived
(MD Q08-2)
RN Q06-2
vs RN Q082
MD Q06-2
vs MD Q082
1%
0.997
5%
0.870
0.01
19%
0.897
0.008
59%
0.538
0.498
16%
0.493
0
Two-Sample t-test (CI 95%)
MD Q06-2 vs MD Q08-2
RN Q06-2 vs MD Q06-2
Not Equal
Not Equal
(p value 0.000)
(p value 0.002)
MD Q06-2 > MD Q08-2
RN Q06-2 < MD Q06-2
RN Q06-2
vs MD
Q06-2
0.010
0.046
0.018
0.717
RN Q08-2
vs MD Q082
0.667
0.378
0.010
0.000
RN Q08-2 vs MD Q08-1
Equal
(p value 0.070)
RN Q08-2 = MD Q08-2
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
147
RN Q06-2 vs RN Q08-2
Equal
(p value 0.747)
RN Q06-2 = RN Q08-2
Two-proportions test (CI 95%)
Table 52: Results on Impact of Supportive Physician Behavior (Q06-3) - Increase motivation
% Response
Strongly Disagree
Disagree
Neutral
Agree
Strongly Agree
RN Actual
(RN Q06-3)
RN Perceived
(RN Q08-3)
MD Actual
(MD Q063)
1%
5%
8%
43%
42%
1%
5%
11%
49%
34%
0%
1%
10%
46%
43%
MD Perceived
(MD Q08-3)
RN Q06-3
vs RN Q083
MD Q06-3
vs MD Q083
1%
0.997
4%
0.715
0.017
21%
0.322
0.006
57%
0.127
0.036
18%
0.045
0
Two-Sample t-test (CI 95%)
MD Q06-3 vs MD Q08-3
RN Q06-3 vs MD Q06-3
Not Equal
Equal
(p value 0.000)
(p value 0.091)
MD Q06-3 > MD Q08-3
RN Q06-3 = MD Q06-3
RN Q06-3
vs MD
Q06-3
0.001
0.497
0.556
0.788
RN Q08-3
vs MD Q083
0.531
0.838
0.005
0.115
0.000
RN Q08-3 vs MD Q08-3
Not Equal
(p value 0.002)
RN Q08-3 > MD Q08-3
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
148
RN Q06-3 vs RN Q08-3
Equal
(p value 0.203)
RN Q06-3 = RN Q08-3
Two-proportions test (CI 95%)
Table 53: Results on Impact of Supportive Physician Behavior (Q06-4) - Increase job satisfaction
% Response
Strongly Disagree
Disagree
Neutral
Agree
Strongly Agree
RN Actual
(RN Q06-4)
RN Perceived
(RN Q08-4)
MD Actual
(MD Q064)
2%
5%
5%
43%
45%
1%
6%
9%
50%
33%
0%
1%
8%
48%
43%
MD Perceived
(MD Q08-4)
RN Q06-4
vs RN Q084
MD Q06-4
vs MD Q084
1%
0.476
4%
0.716
0.017
23%
0.039
0.08
52%
0.083
0.498
19%
0.004
0
Two-Sample t-test (CI 95%)
MD Q06-4 vs MD Q08-4
RN Q06-4 vs MD Q06-4
Not Equal
Equal
(p value 0.000)
(p value 0.201)
MD Q06-4 > MD Q08-4
RN Q06-4 = MD Q06-4
RN Q06-4
vs MD
Q06-4
0.001
0.196
0.273
0.668
RN Q08-4
vs MD Q084
0.944
0.482
0.000
0.740
0.000
RN Q08-4 vs MD Q08-4
Not Equal
(p value 0.001)
RN Q08-4 > MD Q08-4
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
149
RN Q06-4 vs RN Q08-4
Not Equal
(p value 0.035)
RN Q06-4 > RN Q08-4
Two-proportions test (CI 95%)
Table 54: Results on Impact of Supportive Physician Behavior (Q06-5) - Increase Commitment toward nursing
% Response
Strongly Disagree
Disagree
Neutral
Agree
Strongly Agree
RN Actual
(RN Q06-5)
RN Perceived
(RN Q08-5)
MD Actual
(MD Q065)
1%
5%
8%
45%
41%
1%
5%
12%
48%
33%
0%
1%
15%
48%
36%
MD Perceived
(MD Q08-5)
RN Q06-5
vs RN Q085
MD Q06-5
vs MD Q085
1%
0.704
5%
0.708
0.018
27%
0.130
0.007
53%
0.458
0.296
14%
0.049
0
Two-Sample t-test (CI 95%)
MD Q06-5 vs MD Q08-5
RN Q06-5 vs MD Q06-5
Not Equal
Equal
(p value 0.000)
(p value 0.806)
MD Q06-5 > MD Q08-5
RN Q06-5 = MD Q06-5
RN Q06-5
vs MD
Q06-5
0.012
0.021
0.585
0.271
RN Q08-5
vs MD Q085
0.795
0.989
0.000
0.291
0.000
RN Q08-5 vs MD Q08-5
Not Equal
(p value 0.000)
RN Q08-5 > MD Q08-5
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
150
RN Q06-5 vs RN Q08-5
Equal
(p value 0.054)
RN Q06-5 = RN Q08-5
Two-proportions test (CI 95%)
APPENDIX F4: RESULTS OF ACTUAL VS PERCEIVED NORMS OF DISRUPTIVE
PHYSICIAN BEHAVIORS
Table 55: Results on Disruptive Physician Behavior (Q09-1) - Being verbally abusive
% Response
Two-proportions test (CI 95%)
RN Q11-1
vs MD
Q11-1
MD
Perceived
(MD Q11-1)
RN Q09-1
vs RN
Q11-1
MD Q09-1
vs MD
Q11-1
RN Q09-1
vs MD
Q09-1
23%
0.000
0
0.000
0.414
Never
74%
26%
Few
Seldom
21%
46%
9%
70%
0.000
0
0.000
0.000
Some
5%
25%
0%
6%
0.000
0
0.000
0.000
Most
About Half the
time
Usually
0%
2%
0%
1%
-
-
-
0.272
Everyone
Always
0%
0%
0%
0%
-
-
-
-
RN Actual
(RN Q091)
RN
Perceived
(RN Q11-1)
Two-Sample t-test (CI 95%)
RN Q09-1 vs RN Q11-1
MD Q09-1 vs MD Q11-1
RN Q09-1 vs MD Q09-1
RN Q11-1 vs MD Q11-1
Not equal
(p value 0.000)
RN Q09-1 < RN Q11-1
Not Equal
(p value 0.000)
MD Q09-1 < MD Q11-1
Not Equal
(p value 0.000)
RN Q09-1 > MD Q09-1
Not Equal
(p value 0.002)
RN Q11-1 > MD Q11-1
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate
hypothesis.
151
None
MD
Actual
(MD
Q09-1)
91%
RN
MD Response
Response
Table 56: Results on Disruptive Physician Behavior (Q09-2) - Shouting when makes a mistake
% Response
Two-proportions test (CI 95%)
RN Q11-2
vs MD
Q11-2
MD
Perceived
(MD Q11-2)
RN Q09-2
vs RN
Q11-2
MD Q09-2
vs MD
Q11-2
RN Q09-2
vs MD
Q09-2
26%
0.000
0
0.000
0.892
None
Never
76%
26%
MD
Actual
(MD
Q09-2)
95%
Few
Seldom
20%
50%
5%
69%
0.000
0
0.000
0.000
Some
4%
22%
0%
4%
0.000
-
0.001
0.000
Most
About Half the
time
Usually
0%
2%
0%
1%
0.013
-
-
-
Everyone
Always
0%
0%
0%
1%
-
-
-
-
RN
MD Response
Response
RN Actual
(RN Q092)
RN
Perceived
(RN Q11-2)
152
Two-Sample t-test (CI 95%)
RN Q09-2 vs RN Q11-2
MD Q09-2 vs MD Q11-2
RN Q09-2 vs MD Q09-2
RN Q11-2 vs MD Q11-2
Not equal
(p value 0.000)
RN Q09-2 < RN Q11-2
Not Equal
(p value 0.000)
MD Q09-2 < MD Q11-2
Not Equal
(p value 0.000)
RN Q09-2 > MD Q09-2
Not Equal
(p value 0.001)
RN Q11-2 > MD Q11-2
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate
hypothesis.
Table 57: Results on Disruptive Physician Behavior (Q09-3) - Taking feelings of anger out of nurses
% Response
RN
MD Response
Response
RN Actual
(RN Q093)
RN
Perceived
(RN Q11-3)
MD
Actual
(MD
Q09-3)
Two-proportions test (CI 95%)
MD
Perceived
(MD Q11-3)
RN Q09-3
vs RN
Q11-3
MD Q09-3
vs MD
Q11-3
RN Q09-3
vs MD
Q09-3
RN Q11-3
vs MD
Q11-3
Never
50%
18%
56%
14%
0.000
0
0.231
0.229
Few
Seldom
40%
45%
44%
68%
0.171
0
0.383
0.000
Some
9%
33%
1%
17%
0.000
0
0.000
0.000
Most
About Half the
time
Usually
1%
4%
0%
1%
0.018
-
0.082
0.031
Everyone
Always
0%
0%
0%
0%
-
-
-
-
Two-Sample t-test (CI 95%)
RN Q09-3 vs RN Q11-3
MD Q09-3 vs MD Q11-3
RN Q09-3 vs MD Q09-3
RN Q11-3 vs MD Q11-3
Not equal
(p value 0.000)
RN Q09-3 < RN Q11-3
Not Equal
(p value 0.000)
MD Q09-3 < MD Q11-3
Not Equal
(p value 0.003)
RN Q09-3 > MD Q09-3
Not Equal
(p value 0.004)
RN Q11-3 > MD Q11-3
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate
hypothesis.
153
None
Table 58: Results on Disruptive Physician Behavior (Q09-4) - Not responding in a timely manner
% Response
RN
MD Response
Response
RN Actual
(RN Q094)
RN
Perceived
(RN Q11-4)
MD
Actual
(MD
Q09-4)
Two-proportions test (CI 95%)
MD
Perceived
(MD Q11-4)
RN Q09-4
vs RN
Q11-4
MD Q09-4
vs MD
Q11-4
RN Q09-4
vs MD
Q09-4
RN Q11-4
vs MD
Q11-4
Never
31%
12%
41%
7%
0.000
0
0.030
0.054
Few
Seldom
44%
41%
59%
72%
0.529
0.005
0.001
0.000
Some
22%
39%
1%
19%
0.000
0
0.000
0.000
Most
About Half the
time
Usually
2%
7%
0%
1%
0.006
-
-
0.000
Everyone
Always
0%
1%
0%
1%
0.373
-
-
-
Two-Sample t-test (CI 95%)
RN Q09-4 vs RN Q11-4
MD Q09-4 vs MD Q11-4
RN Q09-4 vs MD Q09-4
RN Q11-4 vs MD Q11-4
Not equal
(p value 0.000)
RN Q09-4 < RN Q11-4
Not Equal
(p value 0.000)
MD Q09-4 < MD Q11-4
Not Equal
(p value 0.000)
RN Q09-4 > MD Q09-4
Not Equal
(p value 0.000)
RN Q11-4 > MD Q11-4
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate
hypothesis.
154
None
Table 59: Impact of Disruptive Physician Behavior (Q10-1) - Increases delays in care
% Response
Two-proportions test (CI 95%)
RN Actual
(RN Q10-1)
RN Perceived
(RN Q12-1)
MD Actual
(MD Q101)
MD Perceived
(MD Q12-1)
RN Q10-1
vs RN Q121
MD Q10-1
vs MD Q121
RN Q10-1
vs MD Q101
RN Q12-1
vs MD Q121
Strongly Disagree
5%
1%
6%
2%
0.019
0.061
0.700
0.754
Disagree
6%
4%
10%
14%
0.333
0.193
0.194
0.001
Neutral
15%
10%
28%
26%
0.812
0.684
0.001
0.000
Agree
50%
59%
37%
48%
0.048
0.042
0.005
0.021
Strongly Agree
24%
26%
20%
10%
0.690
0.014
0.311
0.000
155
Two-Sample t-test (CI 95%)
RN Q10-1 vs RN Q12-1
MD Q10-1 vs MD Q12-1
RN Q10-1 vs MD Q10-1
RN Q12-1 vs MD Q12-1
Not equal
(p value 0.011)
RN Q10-1 < RN Q12-1
Equal
(p value 0.649)
MD Q10-1 = MD Q12-1
Not Equal
(p value 0.011)
RN Q10-1 > MD Q10-1
Not Equal
(p value 0.000)
RN Q12-1 > MD Q12-1
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
Table 60: Impact of Disruptive Physician Behavior (Q10-2) - Increases incidence of medical error
% Response
Strongly Disagree
Disagree
Neutral
Agree
Strongly Agree
RN Actual
(RN Q10-2)
RN Perceived
(RN Q12-2)
MD Actual
(MD Q102)
5%
14%
29%
34%
19%
2%
8%
20%
46%
24%
8%
15%
28%
31%
17%
MD Perceived
(MD Q12-2)
RN Q10-2
vs RN Q122
MD Q10-2
vs MD Q122
5%
0.188
0.276
15%
0.028
0.982
28%
0.013
0.963
42%
0.004
0.054
10%
0.177
0.06
Two-Sample t-test (CI 95%)
MD Q10-2 vs MD Q12-2
RN Q10-2 vs MD Q10-2
Equal
Equal
(p value 0.892)
(p value 0.235)
MD Q10-2 = MD Q12-2
RN Q10-2 = MD Q10-2
RN Q10-2
vs MD
Q10-2
0.200
0.670
0.936
0.593
0.700
RN Q12-2
vs MD Q122
0.218
0.021
0.045
0.351
0.000
RN Q12-2 vs MD Q12-2
Not Equal
(p value 0.000)
RN Q12-2 > MD Q12-2
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
156
RN Q10-2 vs RN Q12-2
Not equal
(p value 0.000)
RN Q10-2 < RN Q12-2
Two-proportions test (CI 95%)
Table 61: Impact of Disruptive Physician Behavior (Q10-3) - Increases frustration
% Response
Strongly Disagree
Disagree
Neutral
Agree
Strongly Agree
RN Actual
(RN Q10-3)
RN Perceived
(RN Q12-3)
MD Actual
(MD Q103)
3%
3%
10%
42%
42%
1%
1%
7%
48%
44%
4%
6%
14%
46%
29%
MD Perceived
(MD Q12-3)
RN Q10-3
vs RN Q123
MD Q10-3
vs MD Q123
2%
0.027
0.304
5%
0.105
0.882
13%
0.139
0.744
64%
0.172
0.001
16%
0.668
0.003
Two-Sample t-test (CI 95%)
MD Q10-3 vs MD Q12-3
RN Q10-3 vs MD Q10-3
Equal
Not Equal
(p value 0.616)
(p value 0.014)
MD Q10-3 = MD Q12-3
RN Q10-3 > MD Q10-3
RN Q10-3
vs MD
Q10-3
0.575
0.195
0.233
0.401
0.011
RN Q12-3
vs MD Q123
0.185
0.019
0.044
0.001
0.000
RN Q12-3 vs MD Q12-3
Not Equal
(p value 0.000)
RN Q12-3 > MD Q12-3
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
157
RN Q10-3 vs RN Q12-3
Not equal
(p value 0.016)
RN Q10-3 < RN Q12-3
Two-proportions test (CI 95%)
Table 62: Impact of Disruptive Physician Behavior (Q10-5) - Increase Intent to leave job
% Response
Strongly Disagree
Disagree
Neutral
Agree
Strongly Agree
RN Actual
(RN Q10-5)
RN Perceived
(RN Q12-5)
MD Actual
(MD Q105)
8%
11%
20%
33%
29%
1%
3%
16%
47%
33%
8%
9%
23%
31%
29%
MD Perceived
(MD Q12-5)
RN Q10-5
vs RN Q125
MD Q10-5
vs MD Q125
5%
0.000
0.195
8%
0.000
0.839
23%
0.241
0.975
49%
0.000
0.001
15%
0.312
0.002
Two-Sample t-test (CI 95%)
MD Q10-5 vs MD Q12-5
RN Q10-5 vs MD Q10-5
Equal
Equal
(p value 0.865)
(p value 0.960)
MD Q10-5 = MD Q12-5
RN Q10-5 = MD Q10-5
RN Q10-5
vs MD
Q10-5
0.880
0.512
0.458
0.769
0.969
RN Q12-5
vs MD Q125
0.034
0.018
0.071
0.669
0.000
RN Q12-5 vs MD Q12-5
Not Equal
(p value 0.000)
RN Q12-5 > MD Q12-5
Note: Two-sample t test were hypothesized for 'Responses are Equal'. P value less than 0.05 indicates accept alternate hypothesis.
158
RN Q10-5 vs RN Q12-5
Not equal
(p value 0.000)
RN Q10-5 < RN Q12-5
Two-proportions test (CI 95%)
159
APPENDIX G
ADDITIONAL FINDINGS
160
Do physicians display supportive behaviors toward nurses?
The nurses were presented with examples of supportive physician behaviors
(SPB) and were asked how many physicians displayed those behaviors to them. They
were also asked about their perceptions of other nurses’ response regarding these same
questions. The response type for these questions were none (1), few (2), some (3), most
(4) and everyone (5).
The physicians were presented with the same examples of supportive behaviors
and were asked how frequently they demonstrated those behaviors toward nurses.
Physicians were also asked about their perceptions of other physicians’ behaviors
regarding the same questions. The responses for these questions were never (1), seldom
(2), about half the time (3), usually (4) and always (5).
The responses of the nurses and the physicians were examined using 1-sample ttest. The most favorable responses that were found statistically true were summarized in
Table 61 for each questions. Here, µ indicates sample mean. For example, 4 < µ < 5 for
RN data sets demonstrates the sample mean was found statistically significant for more
than ‘most (4)’ but less than ‘everyone (5)’. From the Table 63, it is evident that more
than ‘some’ MDs demonstrate supportive behaviors toward nurses as the RNs
experienced and perceived. And the MDs demonstrate the supportive behaviors toward
nurses more than ‘usually’. Thus, null hypothesis of hypothesis – 6 was found to be
rejected for ‘some’ physicians.
161
Table 63: Results of 1-Sample t-Test for Hypothesis 6
Supportive Physician Behaviors
Cooperative behavior toward nurses
Correct nurses in a supporting
manner if they make a mistake
Act supportive to nurses who are
stressed or frustrated
Responsive to nurses concerns in a
timely manner
RN
Actual
4<µ<5
RN
Perceived
3<µ<4
4<µ<5
MD
Perceived
3<µ<4
3<µ<4
3<µ<4
4<µ<5
3<µ<4
3<µ<4
3<µ<4
4<µ<5
3<µ<4
3<µ<4
3<µ<4
4<µ<5
3<µ<4
MD Actual
Additional Findings – Do physicians display disruptive behaviors toward nurses?
Physician disruptive behaviors were also examined. Table 64 demonstrates the
findings of this analysis. According to the table, null hypothesis of hypothesis – 7 was
found to be rejected for ‘few’ physicians.
Table 64: Results of 1-Sample t-Test for Hypothesis 7
Disruptive Physician Behaviors
Abusive behavior toward nurses.
Shouting or yelling at nurses if they
make a mistake.
Taking feelings of anger, stress, or
frustration out on nurses.
Not responding to nurses concerns
in a timely manner.
RN
Actual
1<µ<2
RN
Perceived
1<µ<2
MD
Actual
1<µ<2
MD
Perceived
1<µ<2
1<µ<2
1<µ<2
1<µ<2
1<µ<2
1<µ<2
2<µ<3
1<µ<2
1<µ<2
1<µ<2
2<µ<3
1<µ<2
2<µ<3
162
Additional Findings – Effects of Physicians Behaviors on Nursing Outcomes
After presenting the supportive behaviors and disruptive behaviors by physicians,
the RNs and the MDs were asked if those behaviors had any effect on few nursing
outcomes. They were also asked about their perceptions of coworkers’ opinion regarding
these same questions. The responses were collected using a 5 – point Likert type scale of
Strongly Disagree (1) to Strongly Agree (5). Initially, 1-sample t-test was conducted
against the target mean 3 (Neutral). A sample mean greater than 3 in 1-sample t-test
would indicate agree, i.e. physicians behaviors do have impact on nursing outcomes.
Table 65 demonstrates the findings of this analysis. According to the table, null
hypothesis of hypothesis – 8 was found to be rejected for both supportive and disruptive
behaviors.
Table 65: Results of 1-Sample t-Test for Hypothesis 8
Supportive Physician Behaviors
Increases nurses’ motivation toward
their job.
Increases nurses’ satisfaction with
their job
Increases the commitment of nurses
toward their profession
Disruptive Physician Behaviors
Increases nurse’s frustration.
Decreases job dissatisfaction of
nurses.
Increases nurse’s intention to leave
their job.
RN
Actual
RN
Perceived
MD Actual
MD
Perceived
4<µ<5
4<µ<5
4<µ<5
3<µ<4
4<µ<5
4<µ<5
4<µ<5
3<µ<4
4<µ<5
3<µ<4
4<µ<5
3<µ<4
RN
Actual
4<µ<5
RN
Perceived
4<µ<5
3<µ<4
3<µ<4
3<µ<4
MD
Perceived
3<µ<4
4<µ<5
3<µ<4
3<µ<4
4<µ<5
3<µ<4
3<µ<4
MD Actual
163
Additional Findings – Effects of Physicians Behaviors on Clinical Outcomes
Similar to previous section, effect of physicians’ behaviors on perceived clinical
outcomes were examined. The response type for this section was a 5-point Likert type
scale – strongly disagree (1) to strongly agree (5). Table 66 demonstrates the findings of
this analysis. Null hypothesis of hypothesis 9 was found to be rejected, i.e. physicians’
behaviors have significant effect on perceived clinical outcomes.
Table 66: Results of 1-Sample t-Test for Hypothesis 9
Reduces delays in care
3<µ<4
RN
Perceived
3<µ<4
Reduces incidence of medical error
3<µ<4
3<µ<4
Supportive Physician Behaviors
Disruptive Physician Behaviors
Increases delays in care.
Increases incidence of medical
errors.
RN Actual
3<µ<4
RN
Perceived
3<µ<4
3<µ<4
3<µ<4
RN Actual
4<µ<5
MD
Perceived
3<µ<4
4<µ<5
3<µ<4
MD Actual
3<µ<4
MD
Perceived
3<µ<4
3<µ<4
3<µ<4
MD Actual
164
APPENDIX H
RECOMMENDED INSTRUMENT
165
166
167
168
169
170